EP2153438B1 - Post-processing for reducing quantification noise of an encoder during decoding - Google Patents
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
- G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
- G10L19/26—Pre-filtering or post-filtering
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
- G10L21/0316—Speech enhancement, e.g. noise reduction or echo cancellation by changing the amplitude
- G10L21/0364—Speech enhancement, e.g. noise reduction or echo cancellation by changing the amplitude for improving intelligibility
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- G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
- G10L21/0208—Noise filtering
Definitions
- the present invention relates to signal processing, in particular digital audio signals in the field of telecommunications, these signals being for example speech, music, or other signals.
- the rate needed to pass an audio and / or video signal with sufficient quality is an important parameter in telecommunications.
- audio coders have been developed in particular to compress the amount of information necessary to transmit a signal.
- Some encoders achieve particularly high information compression rates. Such coders generally use advanced information modeling and quantification techniques. Thus, such encoders transmit only models or partial data of the signal.
- the decoded signal although not identical to the original signal (since some of the information has not been transmitted due to the quantization operation), nevertheless remains very close to the original signal.
- Quantization noise The difference, from a mathematical point of view, between the decoded signal and the original signal is then called "quantization noise”.
- disortion introduced by the coding / decoding.
- a perceptual post-filter of the type used, for example, in CELP type speech decoders (for "Code Excited Linear Prediction"). This is to perform a filtering that improves the subjective quality at the price of a distortion. Indeed, a signal attenuation is applied in the areas where the quantization noise is most audible (especially between the formants).
- Current perceptual post-filters provide good results for speech signals, but poorer results for other types of signals (music signals, for example).
- Harmonics and formants are well-known spectral characteristics of speech but applying this type of processing to a signal other than speech generates strong distortions. For example, the spectral richness of a music signal can not be handled with such a simple signal model.
- perceptual post-filters can generate distortions, because they rely on a model that is not precise enough. Moreover, the perceptual post filter is usually ineffective in periods of silence.
- the document US2003 / 0182104 describes the modification of a digital audio signal in a decoding step based on a psychoacoustic model. Such a modification would be applicable to the perceptually encoded signals provided that the quantization noise distribution can be derived from the encoded data.
- Another treatment family targets conventional noise reduction treatments to distinguish the useful signal from the noise.
- This type of processing therefore makes it possible to reduce the noise related to the environment of the signal capture and it is often used for speech signals.
- coding / decoding one may want to transmit the ambient noise and it is then desirable that the noise reduction does not apply to this type of noise.
- the present invention improves the situation.
- noise reduction processing is understood to mean an operation of the type described above which consists in extracting the useful signal from a signal to be processed, by filtering the parasitic signals, for example by defining a gain function intervening in a filter applied to the decoded signal.
- the quantization noise is filtered.
- noise reduction processing specific to each type of compression coding performed.
- the very way of estimating the characteristics of the noise reduction filter depends on the type of coding performed.
- the quantization noise itself strongly depends on the type of coding performed. It will be seen that it is possible to establish a variation of the quantization noise as a function of a variation of the decoded signal, and that this variation of the quantization noise is specific to the type of coding implemented.
- the prior information on the type of compression coding is obtained during an encoder declaration procedure.
- the invention is particularly suitable in the case where the type of compression coding is a coding according to the G.711 standard.
- the present invention also provides a device for processing a signal initially coded in compression according to a predetermined type of coding, and then decoded.
- the device is defined in claim 6.
- the device advantageously comprises means for implementing the method described above.
- FIG. figure 1 representing a TBQ device of the aforementioned type downstream of the DEC decoding unit. This figure 1 will be described in detail later.
- the present invention also relates to a computer program, intended to be stored in memory of a processing device of the aforementioned type, and comprising instructions for calculating the quantization noise, as well as parameters of a quantization noise reduction filter. when these instructions are executed by a processor of the processing device.
- the instructions on the variation of the quantization noise can be programmed offline, on the basis of observations (theoretical or experimental according to the exemplary embodiments which will be described later) made on the type of coding used.
- the way in which these instructions are carried out, itself, will be described in detail later, with reference to figures 2 and 5 which can then constitute flowcharts of a computer program within the meaning of the invention.
- the invention proposes a post-processing performed after decoding and which uses information a priori on the characteristics of the quantization operation performed by the encoder.
- the type of processing (or "processing model" according to the generic terms above) that will be chosen to process the signal is independent of the characteristics of the signal itself.
- the processing itself in particular the estimation of the gain function
- the type of treatment is the same and is not based, for example, on only on the energy of a decoded frame received.
- the invention makes it possible to reduce the quantization noise (and therefore the distortion) that a compression encoder of the signal implementing a quantization operation usually introduces.
- the invention advantageously reduces the quantization noise alone, even during periods of silence, and this, for any type of signal.
- the implementation of the invention does not perform a conventional noise reduction and therefore does not modify the noise related to the environment of the capture of the signal.
- the implementation of the invention can reduce or eliminate quantization noise without distorting the signal and this for any type of signal, just using a priori information on the type of encoder used (for example the characteristics of the encoder compression model, the characteristics of the quantizer, or other).
- the present invention finds an advantageous application to the field of speech and music processing, and more generally to the processing of the signal, especially images, since any encoder is required to introduce a quantization noise.
- the invention applies to all areas where it is sought to reduce a quantization noise of a signal.
- the signal thus decoded denoted S * , then has a quantization noise which is defined mathematically as a difference (S * - S) with respect to the original signal S.
- a quantization noise reduction processing unit TBQ is provided, downstream of the decoder DEC, for suppressing or at least limiting the quantization noise in the signal S * .
- the unit TBQ comprises at least one input E to receive decoder DEC information INF on the type of coding / decoding implemented, which then allows to choose a noise reduction treatment model to be implemented. artwork.
- it is estimated from the signal received and decoded S * and, depending on the type of coding / decoding that has been implemented, the influence of the quantization noise in the received signal S * .
- a calculation module is provided to give an estimate of the quantization noise BQ, on the basis of the model chosen and as a function of the received signal S * .
- This calculation module can typically be in the form of a combination of a processor and a working memory (not shown).
- the estimated noise BQ is simply processed by applying a conventional filtering FIL to the signal S * to finally output a processed signal S * T.
- the parameters PAR of the FIL filter applied to the signal S * are determined to reduce in particular the estimated quantization noise BQ.
- step S3 determining a model (step S3) of noise reduction processing.
- the quantization noise reduction model chosen may be different, for example depending on whether the signal has been coded / decoded according to the G.711 standard or coded / decoded according to the standard. G.722.
- step S4 when the signal is received in successive blocks (or frames marked TRi in step S1), it is estimated (step S4) a quantization noise level specific to the chosen model.
- a quantization noise level specific to the chosen model.
- This RSB information depends on the decoded signal S * , but also the type of coding implemented.
- prior knowledge of the coding by obtaining the information INF allows, together with certain statistical characteristics of the signal S * , to estimate here the signal-to-noise ratio RSB.
- This step S4 therefore requires knowing a priori the type of encoder that has been used, information that can be obtained for example during a declaration procedure of the encoder called "encoder transaction", which is supposed to be acquired.
- the type of encoder, the characteristics of its compression model and its quantizer Q make it possible to estimate an evolution of the signal-to-quantization noise ratio, as a function of certain statistical parameters of the signal, for example its variance, its spectral density of power, or others.
- This relationship between the signal-to-quantization noise ratio and the statistical parameters of the signal involves coder-specific laws which will be described later, for some exemplary embodiments.
- the necessary statistical parameters can be calculated by classical quantity estimators (eg variance). Based on these estimates, an estimate of the signal to noise quantization ratio can be extrapolated.
- the estimates can be made indifferently in the time domain, frequency, or any other time-frequency domain (wavelet for example).
- next step S5 consists in calculating the filter parameters for the reduction of the quantization noise in the received signal S * .
- Knowledge of the signal-to-noise ratio makes it possible to deduce the expression of a quantization noise reduction filter, this filter being hereinafter called "post-filter” (downstream of the decoder). It is indeed possible to deduce the expression of a digital filter whose purpose is to reduce a noise whose most characteristics are known a priori (its power spectral density for example) and whose level is determined from the estimation of the quantization signal-to-noise ratio obtained at step previous S4.
- the calculation of the filter can be carried out in the frequency domain and implement any short-term spectral attenuation technique (a spectral subtraction, a Wiener filter, or other).
- the calculation of the post-filter in step S5 can be performed in the time domain, frequency domain, or any other time-frequency domain.
- step S6 itself, here amounts to filtering the decoded signal S * by the post-filter calculated in step S5.
- This step S6 can be performed in the time or frequency domain, according to the constraints related to the implementation and the estimation domain of the PAR parameters and the RSB ratio in the previous steps.
- a TRi 'frame processed by denoising the quantization noise in step S7 is obtained.
- RSB quantization signal-to-noise ratio
- Expression (1) is strongly dependent on the value of this parameter ⁇ .
- ⁇ the maximum signal-to-noise ratio is obtained for a full-scale signal and decreases rapidly if the signal amplitude decreases.
- the first variation of the compression law (0 ⁇
- the implementation of the quantization noise reduction processing is based on the exploitation of this information a priori. In particular, it requires an estimation of the load factor ⁇ , the parameter on which the power of the quantization noise depends, as follows.
- a variant of the treatment presented here is to reduce the quantization noise, sample by sample, rather than a treatment by successive blocks.
- the load factor is directly given by the amplitude level of the sample (inverse of the square root of the amplitude) and the continuation of the treatment is similar to that presented above.
- the ITU-T G.722 coding standardized in 1988 for 64 kbit / s digital audio conferencing applications, is still very widely used. It is a hierarchical coding / decoding at three rates: 64, 56 and 48 kbit / s.
- the signal is divided into two subbands by a filter called QMF (for "Quadrature Mirror Filter”).
- QMF for "Quadrature Mirror Filter”
- ADPCM encoder for "Adaptive Differential Pulse Code Modulation"
- the high band is coded on 2 bits per sample.
- the difference between the three bit rates comes from the low band which is coded on 6 bits per sample for the highest bitrate, but it is possible to reserve the last or the last two bits for data transmission.
- the quality of the higher bit rate is very good, but the coding noise becomes very audible and annoying for the lowest bit rate at 48 kbit / s.
- the quantization noise reduction processing in the sense of the invention can be advantageously applied in this case.
- the quantization noise spectrum (solid line curve) is always flat, regardless of the signal spectrum (dotted line curve).
- the signal to quantization noise ratio depends on the average signal strength and its nature.
- the RSB ratio correlates well with the average power of the signal S * .
- the RSB ratio was estimated on segments of 80 samples (5 ms for a sampling frequency of 16 kHz).
- the representation in the form of point clouds of the figure 8 illustrates even better the correlation between the average power of the signal (abscissa axis) and the signal-to-quantization noise ratio (y-axis), calculated by segments of 80 samples.
- the figure 9 represents in black on a gray background the areas of the signal where the estimation error of the RSB ratio is greater than 6 dB, and the RSB ratio itself is less than 25 dB, that is to say the signal areas wherein the estimator underestimates the quantization noise, resulting in a lower efficiency of the quantization noise reduction processing. It can nevertheless be noted that these zones correspond to unvoiced signal segments, for which the quantization noise is less troublesome because of the intrinsically noisy nature of the signal.
- the dashed line represents the estimate of the noise power.
- the dashed lines delimit the area where the error of the estimate is less than 6 dB. Below the solid line, the RSB is greater than 25 dB.
- the black dots correspond to the black segments of the figure 9 .
- a very simple estimate of the RSB ratio based solely on the energy of the decoded signal can give good results for ADPCM type coding / decoding.
- the estimation of the RSB ratio can be further refined by taking into account, for example, the prediction gain of the ARMA (autoregressive) filters which intervene in the G.722 decoder.
- the quantization noise reduction process of the invention can be effectively applied for this type of coding / decoding.
- This example is obviously valid for other types of coding / decoding of the same family as those standardized G.726 or G.727.
- an advantageous application of the invention can for example aim to reduce the quantization noise of a standardized ITU-G.711 encoder by using the properties of the quantization law implemented. , especially according to law A in Europe. Indeed, in this application, the quantization noise is white and it is possible to estimate the quantization signal-to-noise ratio and hence a gain function that makes it possible to reduce this noise.
- An advantageous application of the invention thus aims at the reduction of quantization noise in the processing at the extended band extension of the G.711 coder (ITU-T SG16, G.711WB).
- the invention applies to any type of coding / decoding as long as its intrinsic characteristics are known.
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Abstract
Description
La présente invention concerne un traitement de signal, en particulier de signaux audionumériques dans le domaine des télécommunications, ces signaux pouvant être par exemple des signaux de parole, de musique, ou autres.The present invention relates to signal processing, in particular digital audio signals in the field of telecommunications, these signals being for example speech, music, or other signals.
Généralement, le débit nécessaire pour faire transiter un signal audio et/ou vidéo avec une qualité suffisante est un paramètre important en télécommunications. Afin de réduire ce paramètre et d'augmenter alors le nombre de communications possibles via un même réseau, des codeurs audio ont été développés notamment pour compresser la quantité d'informations nécessaire pour transmettre un signal.Generally, the rate needed to pass an audio and / or video signal with sufficient quality is an important parameter in telecommunications. In order to reduce this parameter and then increase the number of possible communications via the same network, audio coders have been developed in particular to compress the amount of information necessary to transmit a signal.
Certains codeurs permettent d'atteindre des taux de compression de l'information particulièrement élevés. De tels codeurs utilisent en général des techniques avancées de modélisation et de quantification de l'information. Ainsi, de tels codeurs ne transmettent que des modèles ou des données partielles du signal.Some encoders achieve particularly high information compression rates. Such coders generally use advanced information modeling and quantification techniques. Thus, such encoders transmit only models or partial data of the signal.
Le signal décodé, bien qu'il ne soit pas identique au signal original (puisqu'une partie de l'information n'a pas été transmise du fait de l'opération de quantification), reste néanmoins très proche du signal original. La différence, du point de vue mathématique, entre le signal décodé et le signal original est alors appelée « bruit de quantification ». On peut parler aussi de « distorsion » introduite par le codage/décodage.The decoded signal, although not identical to the original signal (since some of the information has not been transmitted due to the quantization operation), nevertheless remains very close to the original signal. The difference, from a mathematical point of view, between the decoded signal and the original signal is then called "quantization noise". We can also speak of "distortion" introduced by the coding / decoding.
Les traitements en compression de signaux sont souvent conçus de manière à minimiser le bruit de quantification et, en particulier, à rendre ce bruit de quantification le moins audible possible lorsqu'il s'agit de traiter un signal audio. Il existe alors des techniques prenant en compte les caractéristiques psycho-acoustiques de l'audition, dans le but de « masquer » ce bruit. Toutefois, pour obtenir des débits les plus faibles possibles, le bruit peut demeurer audible, parfois, ce qui, dans certaines circonstances, dégrade l'intelligibilité du signal.Signal compression processes are often designed to minimize quantization noise and, in particular, to make this quantization noise as audible as possible when dealing with an audio signal. There are then techniques taking into account the psycho-acoustic characteristics of hearing, in order to "hide" this noise. However, to obtain flow rates as low as possible, the noise may remain audible, sometimes, which in some circumstances degrades the intelligibility of the signal.
Afin de réduire ce bruit, deux familles de techniques sont habituellement utilisées.In order to reduce this noise, two families of techniques are usually used.
Il est possible, tout d'abord, d'utiliser un post-filtre perceptuel, du type utilisé par exemple dans les décodeurs de parole de type CELP (pour « Code Excited Linear Prediction »). Il s'agit d'effectuer un filtrage qui améliore la qualité subjective au prix d'une distorsion. En effet, on applique une atténuation du signal dans les zones où le bruit de quantification est le plus audible (notamment entre les formants). Les post-filtres perceptuels actuels procurent de bons résultats pour des signaux de parole, mais de moins bons résultats pour d'autres types de signaux (signaux de musique, par exemple).It is possible, first of all, to use a perceptual post-filter, of the type used, for example, in CELP type speech decoders (for "Code Excited Linear Prediction"). This is to perform a filtering that improves the subjective quality at the price of a distortion. Indeed, a signal attenuation is applied in the areas where the quantization noise is most audible (especially between the formants). Current perceptual post-filters provide good results for speech signals, but poorer results for other types of signals (music signals, for example).
En effet, un post-filtre d'amélioration de la parole codée est décrit notamment dans le document Chen et al :
- "
Adaptive Postfiltering for Quality Enhancement of Coded Speech", Chen J.H., Gersho A., IEEE Trans. On Speech and Audio Proc., (janvier 1995
- "
Adaptive Postfiltering for Quality Enhancement of Coded Speech, "Chen JH, Gersho A., IEEE Trans., Speech and Audio Proc., (January 1995).
Le modèle décrit repose sur un découpage en deux sections :
- une section à « long terme » renforce les harmoniques (harmoniques de la fréquence fondamentale) et creuse les vallées spectrales entre ces harmoniques, et
- une section à « court terme » renforce les formants et creuse également les vallées spectrales entre ces formants.
- a "long-term" section reinforces the harmonics (harmonics of the fundamental frequency) and digs the spectral valleys between these harmonics, and
- a "short-term" section reinforces the formants and also widens the spectral valleys between these formants.
Les harmoniques et les formants sont des caractéristiques spectrales bien connues de la parole mais appliquer ce type de traitement sur un autre signal que de la parole génère de fortes distorsions. Par exemple, la richesse spectrale d'un signal de musique ne peut pas être traitée avec un tel modèle simple de signal.Harmonics and formants are well-known spectral characteristics of speech but applying this type of processing to a signal other than speech generates strong distortions. For example, the spectral richness of a music signal can not be handled with such a simple signal model.
Ainsi, les post-filtres perceptuels peuvent générer des distorsions, du fait qu'ils reposent sur un modèle qui n'est pas assez précis. Par ailleurs, le post-filtre perceptuel est généralement inefficace dans les périodes de silence. Ces problèmes ont pu être observés expérimentalement par la Demanderesse qui a cherché dans un premier temps à intégrer ce type de post-filtres perceptuels dans des décodeurs qui ne sont pas de type CELP, par exemple dans des décodeurs au sens de la norme G.711 ou de la norme G.722.Thus, perceptual post-filters can generate distortions, because they rely on a model that is not precise enough. Moreover, the perceptual post filter is usually ineffective in periods of silence. These problems have been observed experimentally by the Applicant who first sought to integrate this type of perceptual post-filters in decoders that are not CELP type, for example in decoders within the meaning of the G.711 standard. or the G.722 standard.
Le document
Une autre famille de traitement vise les traitements classiques de réduction de bruit pour distinguer le signal utile des bruits parasites. Ce type de traitement permet donc de réduire le bruit lié à l'environnement de la capture du signal et il est souvent utilisé pour des signaux de parole. Toutefois, ici, il est impossible de rendre transparent le traitement vis-à-vis du bruit lié à l'environnement de la prise de son, ce qui pose problème pour du codage de signal de musique, notamment. Ainsi, en codage/décodage on peut vouloir transmettre le bruit d'ambiance et il est alors souhaitable que la réduction de bruit ne s'applique pas à ce type de bruit.Another treatment family targets conventional noise reduction treatments to distinguish the useful signal from the noise. This type of processing therefore makes it possible to reduce the noise related to the environment of the signal capture and it is often used for speech signals. However, here, it is impossible to make transparent the treatment vis-à-vis the noise related to the environment of the sound recording, which poses a problem for music signal coding, in particular. Thus, in coding / decoding one may want to transmit the ambient noise and it is then desirable that the noise reduction does not apply to this type of noise.
La présente invention vient améliorer la situation.The present invention improves the situation.
Elle propose à cet effet un procédé de traitement d'un signal qui a été codé en compression selon un type de codage prédéterminé, appliquant une opération de quantification, puis décodé. Le procédé au sens de l'invention est defini dans la revendication 1.To this end, it proposes a method of processing a signal that has been coded in compression according to a predetermined type of coding, applying a quantization operation, and then decoding. The process according to the invention is defined in
On entend ici par le terme « traitement de réduction de bruit » une opération du type décrit ci-avant qui consiste à extraire le signal utile d'un signal à traiter, en filtrant les signaux parasites, par exemple en définissant une fonction de gain intervenant dans un filtre appliqué au signal décodé. Ici, le bruit de quantification est ainsi filtré.Here, the term "noise reduction processing" is understood to mean an operation of the type described above which consists in extracting the useful signal from a signal to be processed, by filtering the parasitic signals, for example by defining a gain function intervening in a filter applied to the decoded signal. Here, the quantization noise is filtered.
Il s'agit donc d'un débruitage classique mais appliqué ici pour réduire le bruit de quantification. Ce débruitage ne s'apparente en aucune manière à un post-filtre perceptuel du type décrit dans Chen et al, lequel s'appuie complètement sur les caractéristiques et la dynamique du signal, tandis que le traitement de réduction de bruit au sens de l'invention s'appuie plutôt sur la détermination du bruit de quantification.It is therefore a classic denoising but applied here to reduce the quantization noise. This denoising is in no way related to a perceptual post-filter of the type described in Chen et al, which relies completely on the characteristics and the dynamics of the signal, while the noise reduction processing in the sense of the The invention relies instead on the determination of the quantization noise.
Ainsi, on prévoit un type de traitement de réduction de bruit propre à chaque type de codage en compression réalisé. La manière même d'estimer les caractéristiques du filtre de réduction de bruit (type de fonction de gain, paramètres de la fonction de gain, etc.) dépend du type de codage réalisé.Thus, there is provided a type of noise reduction processing specific to each type of compression coding performed. The very way of estimating the characteristics of the noise reduction filter (type of gain function, gain function parameters, etc.) depends on the type of coding performed.
On verra en particulier dans les exemples de réalisation donnés ci-après que le bruit de quantification lui-même dépend fortement du type de codage réalisé. On verra qu'il est possible d'établir une variation du bruit de quantification en fonction d'une variation du signal décodé, et que cette variation du bruit de quantification est propre au type de codage mis en oeuvre.It will be seen in particular in the embodiment examples given below that the quantization noise itself strongly depends on the type of coding performed. It will be seen that it is possible to establish a variation of the quantization noise as a function of a variation of the decoded signal, and that this variation of the quantization noise is specific to the type of coding implemented.
Ainsi :
- on estime, à partir des informations sur le type de codage, une variation du bruit de quantification en fonction d'au moins un paramètre du signal décodé, et
- en fonction d'une valeur courante de ce paramètre dans le signal décodé, on estime le bruit de quantification pour déterminer la fonction de filtrage à appliquer au signal décodé ayant cette valeur courante de paramètre.
- it is estimated from the information on the type of coding a variation of the quantization noise according to at least one parameter of the decoded signal, and
- based on a current value of this parameter in the decoded signal, the quantization noise is estimated to determine the filtering function to be applied to the decoded signal having this current parameter value.
On comprendra donc que les informations sur le type de codage en compression sont des informations a priori, indépendantes des caractéristiques du signal et qu'avantageusement, il peut en être déduit :
- un modèle de variation d'un rapport signal à bruit de quantification, en fonction d'au moins un paramètre du signal décodé, et/ou
- une coloration spectrale du bruit de quantification (c'est-à-dire une variation spectrale du bruit de quantification en fonction des caractéristiques du signal décodé).
- a variation model of a signal-to-quantization noise ratio, as a function of at least one parameter of the decoded signal, and / or
- spectral staining of the quantization noise (i.e. spectral variation of the quantization noise as a function of the characteristics of the decoded signal).
Dans un mode possible de réalisation, les informations a priori sur le type de codage en compression sont obtenues lors d'une procédure de déclaration du codeur.In one possible embodiment, the prior information on the type of compression coding is obtained during an encoder declaration procedure.
L'invention est particulièrement adaptée au cas où le type de codage en compression est un codage selon la norme G.711.The invention is particularly suitable in the case where the type of compression coding is a coding according to the G.711 standard.
La présente invention vise aussi un dispositif de traitement d'un signal initialement codé en compression selon un type de codage prédéterminé, puis décodé. Le dispositif est defini dans la revendication 6.The present invention also provides a device for processing a signal initially coded in compression according to a predetermined type of coding, and then decoded. The device is defined in
Plus généralement, le dispositif comporte avantageusement des moyens pour la mise en oeuvre du procédé décrit ci-avant.More generally, the device advantageously comprises means for implementing the method described above.
Il est avantageux qu'un tel dispositif soit intégré dans un décodeur, en aval d'une unité de décodage, comme illustré sur la
La présente invention vise aussi un programme informatique, destiné à être stocké en mémoire d'un dispositif de traitement du type précité, et comportant des instructions pour calculer le bruit de quantification, ainsi que des paramètres d'un filtre de réduction du bruit de quantification, lorsque ces instructions sont exécutées par un processeur du dispositif de traitement.The present invention also relates to a computer program, intended to be stored in memory of a processing device of the aforementioned type, and comprising instructions for calculating the quantization noise, as well as parameters of a quantization noise reduction filter. when these instructions are executed by a processor of the processing device.
Une réalisation avantageuse peut consister à prévoir un jeu d'instructions pour chaque type de codage mis en oeuvre et, dans chaque jeu d'instructions, définir une variation du bruit de quantification en fonction du signal décodé. Ainsi, sur réception des informations a priori, un jeu d'instructions adéquates est sélectionné. Avec ce jeu d'instructions :
- le bruit de quantification présent dans le signal décodé est calculé,
- et les paramètres du post-filtre sont calculés en correspondance de ce bruit de quantification, pour limiter, voire supprimer, ce bruit.
- the quantization noise present in the decoded signal is calculated,
- and the parameters of the post-filter are calculated in correspondence of this quantization noise, to limit or even eliminate this noise.
Les instructions sur la variation du bruit de quantification peuvent être programmées hors ligne, sur la base d'observations (théoriques ou expérimentales d'après les exemples de réalisation qui seront décrits plus loin) faites sur le type de codage utilisé. La manière dont sont exécutées ces instructions, elle-même, sera décrite en détail plus loin, en référence aux
Ainsi, l'invention propose un post-traitement effectué après décodage et qui utilise des informations a priori sur les caractéristiques de l'opération de quantification qu'effectue le codeur. Le type de traitement (ou « modèle de traitement » selon les termes génériques ci-avant) qui sera choisi pour traiter le signal est indépendant des caractéristiques du signal lui-même. Bien entendu, le traitement en soi (notamment l'estimation de la fonction de gain) peut dépendre du signal, par exemple de son énergie ou de sa puissance. En revanche, qu'il s'agisse de traiter un signal de musique, un signal de parole ou tout autre signal (de nature harmonique, impulsive, etc.), le type de traitement est le même et ne se base, par exemple, que sur l'énergie d'une trame décodée reçue. En effet, il est possible de connaître de façon théorique les caractéristiques du bruit de quantification, notamment en fonction de différentes familles de codeurs. Au sens de l'invention, on utilise alors ces informations pour estimer des grandeurs qui sont exploitées pour définir au moins une fonction de gain d'une unité de réduction de bruit qui intervient en aval d'une unité de décodage.Thus, the invention proposes a post-processing performed after decoding and which uses information a priori on the characteristics of the quantization operation performed by the encoder. The type of processing (or "processing model" according to the generic terms above) that will be chosen to process the signal is independent of the characteristics of the signal itself. Of course, the processing itself (in particular the estimation of the gain function) may depend on the signal, for example its energy or its power. On the other hand, whether dealing with a music signal, a speech signal or any other signal (harmonic, impulsive, etc.), the type of treatment is the same and is not based, for example, on only on the energy of a decoded frame received. Indeed, it is possible to know theoretically the characteristics of the quantization noise, in particular according to different families of encoders. For the purposes of the invention, this information is then used to estimate quantities that are exploited to define at least one gain function of a noise reduction unit that operates downstream of a decoding unit.
Ainsi, l'invention permet de réduire le bruit de quantification (et donc la distorsion) qu'introduit habituellement un codeur en compression du signal mettant en oeuvre une opération de quantification.Thus, the invention makes it possible to reduce the quantization noise (and therefore the distortion) that a compression encoder of the signal implementing a quantization operation usually introduces.
Selon l'un des avantages que propose la présente invention, il est possible de garder une même structure de codage/décodage sans y apporter aucune modification et d'assurer pourtant une meilleure qualité du signal décodé, et ce, sans augmenter la quantité d'informations à transmettre par le codeur.According to one of the advantages offered by the present invention, it is possible to keep the same coding / decoding structure without making any changes and yet ensure a better quality of the decoded signal, without increasing the amount of information to be transmitted by the coder.
Selon un autre avantage, l'invention permet de réduire avantageusement le bruit de quantification seul, même en période de silence, et ce, pour tout type de signal.According to another advantage, the invention advantageously reduces the quantization noise alone, even during periods of silence, and this, for any type of signal.
Selon encore un autre avantage, la mise en oeuvre de l'invention n'effectue pas une réduction de bruit classique et donc ne modifie pas le bruit lié à l'environnement de la capture du signal.According to yet another advantage, the implementation of the invention does not perform a conventional noise reduction and therefore does not modify the noise related to the environment of the capture of the signal.
On retiendra en particulier que la mise en oeuvre de l'invention permet de réduire, voire supprimer, le bruit de quantification, sans distordre le signal et ce, pour tout type de signal, simplement en utilisant des informations a priori sur le type de codeur utilisé (par exemple les caractéristiques du modèle de compression du codeur, les caractéristiques du quantificateur, ou autre).We especially remembered that the implementation of the invention can reduce or eliminate quantization noise without distorting the signal and this for any type of signal, just using a priori information on the type of encoder used (for example the characteristics of the encoder compression model, the characteristics of the quantizer, or other).
La présente invention trouve une application avantageuse au domaine du traitement de la parole et de la musique, et plus généralement au traitement du signal, notamment d'images, dès lors qu'un codeur quelconque est amené à introduire un bruit de quantification.The present invention finds an advantageous application to the field of speech and music processing, and more generally to the processing of the signal, especially images, since any encoder is required to introduce a quantization noise.
Plus généralement, l'invention s'applique à tous les domaines où l'on cherche à réduire un bruit de quantification d'un signal.More generally, the invention applies to all areas where it is sought to reduce a quantization noise of a signal.
D'autres caractéristiques et avantages de l'invention apparaîtront à l'examen de la description détaillée ci-après, et des dessins annexés sur lesquels :
- la
figure 1 illustre schématiquement la structure générale d'une unité de traitement au sens de l'invention, - la
figure 2 illustre schématiquement les étapes d'un procédé au sens de l'invention, - la
figure 3 illustre une variation de la loi de compression (dite « loi A ») des amplitudes, dans un codage selon la norme G.711 pour illustrer un exemple de réalisation de l'invention, - la
figure 4 illustre la variation du rapport signal à bruit de quantification RSB en fonction du facteur de charge, cette variation étant tirée de la variation illustrée sur lafigure 3 , - la
figure 5 illustre les étapes d'un exemple de traitement dans le cas d'un codage selon la norme G.711, basé notamment sur les observations des variations desfigures 3 ,et 4 - la
figure 6 illustre un exemple du spectre du signal (courbe en pointillés) et du spectre du bruit de quantification (courbe continue) pour un codage selon la norme G.722, - la
figure 7 illustre un exemple de forme d'onde d'un signal de parole S* (courbe de dessus) et le rapport signal à bruit de quantification correspondant RSB (courbe de dessous), pour un codage/décodage selon la norme G.722, - la
figure 8 est un nuage de points illustrant pour chaque segment de 80 échantillons la corrélation entre le rapport signal à bruit RSB et l'énergie du signal, dans une application à un codage/décodage selon la norme G.722, - la
figure 9 montre les segments de signal (en noir) où l'erreur de l'estimation du rapport signal à bruit de quantification RSB est supérieure à 6 dB tandis que le rapport RSB est inférieur à 25 dB, dans l'application à un codage/décodage selon la norme G.722, - la
figure 10 reprend le nuage de point représentant, pour chaque segment, l'énergie du bruit en fonction de l'énergie du signal, en illustrant ici l'estimation du niveau de bruit (ligne en traits mixtes), la zone ou l'erreur de l'estimation est inférieure à 6 dB (lignes en traits pointillés), et la délimitation pour laquelle le rapport RSB est supérieur 25 dB (ligne en trait plein).
- the
figure 1 schematically illustrates the general structure of a processing unit within the meaning of the invention, - the
figure 2 schematically illustrates the steps of a process within the meaning of the invention, - the
figure 3 illustrates a variation of the compression law (called "law A") of the amplitudes, in a coding according to the G.711 standard to illustrate an embodiment of the invention, - the
figure 4 illustrates the variation of the signal-to-quantization ratio RSB as a function of the load factor, this variation being drawn from the variation illustrated in FIG.figure 3 , - the
figure 5 illustrates the steps of an example of processing in the case of a coding according to the G.711 standard, based in particular on the observations of the variations of theFigures 3 and 4 , - the
figure 6 illustrates an example of the signal spectrum (dotted curve) and the quantization noise spectrum (continuous curve) for G.722 coding, - the
figure 7 illustrates an example of a waveform of a speech signal S * (top curve) and the corresponding quantization noise-to-noise ratio RSB (bottom curve), for coding / decoding according to the G.722 standard, - the
figure 8 is a scatterplot illustrating for each segment of 80 samples the correlation between the SNR signal-to-noise ratio and the signal energy, in an application to G.722 coding / decoding, - the
figure 9 shows the signal segments (in black) where the error of the RSB quantization signal to noise ratio estimate is greater than 6 dB while the RSB ratio is less than 25 dB, in the coding / decoding application according to G.722, - the
figure 10 resumes the point cloud representing, for each segment, the noise energy as a function of the signal energy, illustrating here the estimate of the noise level (phantom line), the zone or the error of the noise. estimate is less than 6 dB (dashed lines), and the bound for which the RSB is greater than 25 dB (solid line).
On se réfère tout d'abord à la
- codé en compression par un codeur COD de type connu et appliquant notamment une opération de quantification Q au signal S,
- transmis via un canal de transmission CA, puis
- décodé par un décodeur DEC homologue du codeur COD.
- encoded in compression by a COD encoder of known type and in particular applying a quantization operation Q to the signal S,
- transmitted via a CA transmission channel, then
- decoded by a decoder DEC homologous coder COD.
Le signal ainsi décodé, noté S*, présente alors un bruit de quantification qui se définit mathématiquement comme un écart (S* - S) par rapport au signal d'origine S.The signal thus decoded, denoted S * , then has a quantization noise which is defined mathematically as a difference (S * - S) with respect to the original signal S.
En référence à nouveau à la
A cet effet, l'unité TBQ comporte au moins une entrée E pour recevoir du décodeur DEC des informations INF sur le type de codage/décodage mis en oeuvre, ce qui permet de choisir alors un modèle de traitement de réduction de bruit à mettre en oeuvre. En particulier, on estime, à partir du signal reçu et décodé S*, et en fonction du type de codage/décodage qui a été mis en oeuvre, l'influence du bruit de quantification dans le signal reçu S*. A cet effet, on prévoit un module de calcul pour donner une estimation du bruit de quantification BQ, sur la base du modèle choisi et en fonction du signal reçu S*. Ce module de calcul peut typiquement se présenter sous la forme d'une combinaison d'un processeur et d'une mémoire de travail (non représentés). A partir du bruit de quantification estimé BQ, on traite simplement le bruit estimé BQ en appliquant un filtrage classique FIL au signal S* pour délivrer finalement un signal traité S* T. Il convient d'insister encore sur le fait que les paramètres PAR du filtre FIL appliqué au signal S* (par exemple une fonction de gain pour le filtrage du signal) sont déterminés pour réduire en particulier le bruit de quantification estimé BQ.For this purpose, the unit TBQ comprises at least one input E to receive decoder DEC information INF on the type of coding / decoding implemented, which then allows to choose a noise reduction treatment model to be implemented. artwork. In particular, it is estimated from the signal received and decoded S * and, depending on the type of coding / decoding that has been implemented, the influence of the quantization noise in the received signal S * . For this purpose, a calculation module is provided to give an estimate of the quantization noise BQ, on the basis of the model chosen and as a function of the received signal S * . This calculation module can typically be in the form of a combination of a processor and a working memory (not shown). From the estimated quantization noise BQ, the estimated noise BQ is simply processed by applying a conventional filtering FIL to the signal S * to finally output a processed signal S * T. It should be further emphasized that the parameters PAR of the FIL filter applied to the signal S * (for example a gain function for the signal filtering) are determined to reduce in particular the estimated quantization noise BQ.
En effet, en référence à la
Ainsi, lorsque le signal est reçu par blocs successifs (ou trames notées TRi à l'étape S1), on estime (étape S4) un niveau du bruit de quantification propre au modèle choisi. Comme on le verra dans les exemples plus loin, il est avantageux d'estimer le niveau de bruit de quantification à partir du calcul du rapport signal à bruit de quantification (noté RSB). Cette information RSB dépend du signal décodé S*, mais aussi du type de codage mis en oeuvre. Ainsi, la connaissance a priori du codage, par l'obtention des informations INF permet, conjointement avec certaines caractéristiques statistiques du signal S*, d'estimer ici le rapport signal sur bruit de quantification RSB.Thus, when the signal is received in successive blocks (or frames marked TRi in step S1), it is estimated (step S4) a quantization noise level specific to the chosen model. As will be seen in the examples below, it is advantageous to estimate the quantization noise level from the calculation of the signal-to-quantization noise ratio (denoted RSB). This RSB information depends on the decoded signal S * , but also the type of coding implemented. Thus, prior knowledge of the coding, by obtaining the information INF allows, together with certain statistical characteristics of the signal S * , to estimate here the signal-to-noise ratio RSB.
Cette étape S4 nécessite donc de connaître a priori le type de codeur ayant été utilisé, information qui peut être obtenue par exemple lors d'une procédure de déclaration du codeur dite « transaction du codeur », que l'on suppose acquise.This step S4 therefore requires knowing a priori the type of encoder that has been used, information that can be obtained for example during a declaration procedure of the encoder called "encoder transaction", which is supposed to be acquired.
Le type de codeur, les caractéristiques de son modèle de compression et de son quantificateur Q permettent d'estimer une évolution du rapport signal à bruit de quantification, en fonction de certains paramètres statistiques du signal, comme par exemple sa variance, sa densité spectrale de puissance, ou autres. Cette relation entre le rapport signal à bruit de quantification et les paramètres statistiques du signal met en jeu des lois propres au codeur qui seront décrites plus loin, pour quelques exemples de réalisations.The type of encoder, the characteristics of its compression model and its quantizer Q make it possible to estimate an evolution of the signal-to-quantization noise ratio, as a function of certain statistical parameters of the signal, for example its variance, its spectral density of power, or others. This relationship between the signal-to-quantization noise ratio and the statistical parameters of the signal involves coder-specific laws which will be described later, for some exemplary embodiments.
Les paramètres statistiques nécessaires peuvent être calculés par des estimateurs de grandeurs classiques (par exemple la variance). En fonction de ces estimations, une estimation du rapport signal à bruit de quantification peut être extrapolée. Les estimations peuvent être réalisées indifféremment dans les domaines temporel, fréquentiel, ou tout autre domaine temps-fréquence (transformée en ondelettes par exemple).The necessary statistical parameters can be calculated by classical quantity estimators (eg variance). Based on these estimates, an estimate of the signal to noise quantization ratio can be extrapolated. The estimates can be made indifferently in the time domain, frequency, or any other time-frequency domain (wavelet for example).
A nouveau en référence à la
Enfin, l'étape de traitement de réduction de bruit S6, proprement dite, revient ici à filtrer le signal décodé S* par le post-filtre calculé à l'étape S5. Cette étape S6 peut être réalisée dans le domaine temporel ou fréquentiel, selon les contraintes liées à la mise en oeuvre et le domaine d'estimation des paramètres PAR et du rapport RSB dans les étapes précédentes. On obtient finalement une trame TRi' traitée par débruitage du bruit de quantification à l'étape S7.Finally, the noise reduction processing step S6, itself, here amounts to filtering the decoded signal S * by the post-filter calculated in step S5. This step S6 can be performed in the time or frequency domain, according to the constraints related to the implementation and the estimation domain of the PAR parameters and the RSB ratio in the previous steps. Finally, a TRi 'frame processed by denoising the quantization noise in step S7 is obtained.
On décrit ci-après un exemple de mise en oeuvre de l'invention pour un codage/décodage selon la norme G.711 (selon la loi européenne dite « loi A »).An exemplary implementation of the invention for coding / decoding according to the G.711 standard (according to the European law called "law A") is described below.
La représentation numérique traditionnelle des signaux monodimensionnels fait appel à une quantification uniforme des échantillons. Ainsi, en l'absence de dépassement de capacité du quantificateur, le rapport signal à bruit (RSB) de quantification dépend de la variance
La grandeur
- x max est le niveau numérique d'amplitude maximum possible d'un échantillon selon le quantificateur choisi, et
- σ x est l'écart-type du signal (la racine carrée de la variance) qui, pour un bloc complet d'échantillons (ou « trame »), peut être estimé par la racine carrée de la puissance moyenne Pm du signal sur ce bloc.
- x max is the maximum possible numerical level of amplitude of a sample according to the quantizer chosen, and
- σ x is the standard deviation of the signal (the square root of the variance) which, for a complete block of samples (or "frame"), can be estimated by the square root of the average power Pm of the signal on that block.
L'expression (1) est fortement dépendante de la valeur de ce paramètre Γ. On constate en particulier que le rapport signal à bruit maximal est obtenu pour un signal en pleine échelle et qu'il décroit rapidement si l'amplitude du signal diminue.Expression (1) is strongly dependent on the value of this parameter Γ. In particular, it can be seen that the maximum signal-to-noise ratio is obtained for a full-scale signal and decreases rapidly if the signal amplitude decreases.
Les limites à bas débits de la loi de quantification uniforme ont amené à développer une loi de quantification dont le rapport signal à bruit de quantification était à peu près indépendant de la variance du signal pour une large dynamique de signaux. C'est bien ce que réalise la loi de quantification logarithmique du codage selon la norme G.711 (dite « loi A » en Europe, ou « loi µ » en Amérique du nord).The low bit rate limits of the uniform quantization law led to the development of a quantization law whose signal to quantization noise ratio was approximately independent of the signal variance for wide signal dynamics. This is what the logarithmic log-quantization law of the G.711 standard (called "A-law" in Europe, or "μ-law" in North America) achieves.
La loi A en usage en Europe est définie par une expression dépendante de la valeur x de l'échantillon quantifié, comme suit :
En référence à la
La loi européenne utilise une valeur de A = 87,56 (qui satisfait numériquement l'équation A/(1 + 1n A) = 16).European law uses a value of A = 87.56 (which numerically satisfies the equation A / (1 + 1n A ) = 16).
A partir de ces observations, il est possible de calculer le rapport signal à bruit de quantification pour une compression selon la loi A, comme suit.From these observations, it is possible to calculate the signal-to-quantization noise ratio for A-law compression as follows.
Pour les signaux de faible intensité (partie uniforme de la loi de compression), la loi A assure un rapport signal à bruit de quantification supérieur (en dB) de 10log(A/(1+ln A)) à celui obtenu par une quantification uniforme sur le même nombre de niveaux, dont l'expression est donnée par :
Pour les signaux de plus grande amplitude (partie logarithmique de la loi de compression), le rapport signal à bruit de quantification est constant et égale 38.16 dB (pour b = 8 bits) :
La
- une première partie croissante, correspondant à la variation uniforme de la loi de compression, et
- une partie suivante, constante, correspondant à la variation logarithmique de cette loi.
- an increasing first portion, corresponding to the uniform variation of the compression law, and
- a following part, constant, corresponding to the logarithmic variation of this law.
Pour traiter la réduction du bruit de quantification introduit par un codage selon la norme G.711, on exploite ici deux informations :
- le rapport signal à bruit de quantification qui est donné par les équations (3) et (4) précédentes, et
- l'information bien connue selon laquelle ce bruit est "blanc" pour ce type de codage.
- the signal-to-noise ratio of quantization given by equations (3) and (4) above, and
- the well known information that this noise is "white" for this type of coding.
La mise en oeuvre du traitement de réduction de bruit de quantification repose sur l'exploitation de ces informations a priori. Elle nécessite notamment de réaliser une estimation du facteur de charge Γ, paramètre dont dépend la puissance du bruit de quantification, comme suit.The implementation of the quantization noise reduction processing is based on the exploitation of this information a priori. In particular, it requires an estimation of the load factor Γ, the parameter on which the power of the quantization noise depends, as follows.
En référence à la
- si le facteur de charge Γ est tel que -20.log(Γ) > -20.log(Γs) = 38.16-64.97∼=-27dB (flèche o en sortie du test T54), alors le rapport signal à bruit de quantification est constant et vaut RSBM ∼= +38dB (plateau de la
figure 4 ), comme fixé à l'étape S55, - sinon (flèche n en sortie du test T54), alors le rapport signal à bruit de quantification RSB peut être calculé selon une variation linéaire en fonction du facteur de charge tirée de l'équation (3) :
- if the load factor Γ is such that -20.log (Γ)> -20.log (Γ s ) = 38.16-64.97~ = -27dB (arrow o at the output of the T54 test), then the signal-to-noise ratio of quantization is constant and is worth RSB M ~ = + 38dB (plateau of the
figure 4 ), as set in step S55, - if not (arrow n at the output of the test T54), then the signal-to-quantization noise ratio RSB can be calculated according to a linear variation as a function of the load factor derived from equation (3):
On évalue ensuite la fonction de gain (étape S57) pour l'application du post-filtre (étape S58). A titre d'exemple purement illustratif, un filtre de Wiener peut être prévu en tant que fonction de gain g(RSB). L'expression du filtre de Wiener f w peut être donnée par la valeur du rapport signal à bruit de quantification RSB calculé précédemment, en tenant compte, bien entendu, de sa dépendance en fréquence avec :
- g(RSB) =f w = RSB / (RSB + 1), où, ici, la valeur RSB ne s'exprime pas en dB mais en valeur naturelle.
- g (RSB) = f w = RSB / (RSB + 1), where, here, the RSB value is not expressed in dB but in natural value.
On peut prévoir avantageusement d'alléger le traitement de réduction de bruit en particulier pour les signaux de faible rapport signal à bruit de quantification, donc à faible niveau d'amplitude (pour des facteurs de charge tels que -20.log(Γ) < -50dB sur la
- un seuillage du post-filtre, et/ou
- un détecteur d'activité vocale pour des signaux de parole (avec un traitement de réduction de bruit de quantification plus léger pendant les périodes d'inactivité vocale).
- a threshold of the post-filter, and / or
- a voice activity detector for speech signals (with lighter quantization noise reduction processing during periods of voice inactivity).
On indique qu'une variante du traitement présenté ici est de réduire le bruit de quantification, échantillon par échantillon, plutôt qu'un traitement par blocs successifs. Dans ce cas, le facteur de charge est directement donné par le niveau d'amplitude de l'échantillon (inverse de la racine carrée de l'amplitude) et la suite du traitement est similaire à celle présentée ci-avant.It is indicated that a variant of the treatment presented here is to reduce the quantization noise, sample by sample, rather than a treatment by successive blocks. In this case, the load factor is directly given by the amplitude level of the sample (inverse of the square root of the amplitude) and the continuation of the treatment is similar to that presented above.
On décrit maintenant une autre application possible de l'invention à un type de codage différent, ici le codage selon la norme G.722.Another possible application of the invention to a different type of coding, here the coding according to the G.722 standard, is described.
Le codage ITU-T G.722, normalisé en 1988 pour les applications d'audioconférence sur canal numérique de 64 kbit/s, est encore très largement utilisé. Il s'agit d'un codage/décodage hiérarchique à trois débits : 64, 56 et 48 kbit/s. Le signal est divisé en deux sous-bandes par un filtre dit QMF (pour « Quadrature Mirror Filter »). Les deux bandes obtenues sont codées avec un codeur MICDA (pour "Modulation par Impulsion et Codage Différentiel Adaptatif"), dit aussi ADPCM en anglais (pour « Adaptive Differential Pulse Code Modulation »).The ITU-T G.722 coding, standardized in 1988 for 64 kbit / s digital audio conferencing applications, is still very widely used. It is a hierarchical coding / decoding at three rates: 64, 56 and 48 kbit / s. The signal is divided into two subbands by a filter called QMF (for "Quadrature Mirror Filter"). The two bands obtained are encoded with an ADPCM encoder (for "Adaptive Differential Pulse Code Modulation").
La bande haute est codée sur 2 bits par échantillon. La différence entre les trois débits vient de la bande basse qui est codée sur 6 bits par échantillon pour le plus haut débit, mais il est possible de réserver le dernier ou les deux derniers bits pour de la transmission de données.The high band is coded on 2 bits per sample. The difference between the three bit rates comes from the low band which is coded on 6 bits per sample for the highest bitrate, but it is possible to reserve the last or the last two bits for data transmission.
La qualité du plus haut débit est très bonne, par contre le bruit de codage devient très audible et gênant pour le débit le plus bas à 48 kbit/s. Le traitement de réduction du bruit de quantification au sens de l'invention peut être avantageusement appliqué dans ce cas.The quality of the higher bit rate is very good, but the coding noise becomes very audible and annoying for the lowest bit rate at 48 kbit / s. The quantization noise reduction processing in the sense of the invention can be advantageously applied in this case.
Déjà, les caractéristiques du bruit de quantification peuvent être efficacement estimées à partir du signal décodé. Comme l'illustre la
La représentation sous forme de nuages de points de la
On peut déduire de cette observation une première règle simple d'estimation du rapport RSB en fonction de la puissance moyenne Pmoy du segment (droite de corrélation représentée en pointillés sur la
On comprendra de cette expression que la puissance moyenne du bruit, déterminée expérimentalement ici, est constante CST = 10 dB, et ce, indépendamment de la puissance moyenne du signal, de sorte que le rapport RSB augmente bien avec la puissance moyenne du signal.It will be understood from this expression that the average noise power, determined experimentally here, is constant CST = 10 dB, and this, independently of the average signal power, so that the RSB ratio increases well with the average power of the signal.
La meilleure estimation du rapport signal à bruit de quantification RSB est obtenue pour les faibles niveaux du signal, c'est-à-dire lorsque le rapport RSB est faible (et donc lorsque le bruit est le plus audible). Cependant, certains segments ont des points situés très en dessous de la ligne en pointillés et l'utilisation de cette règle simple est alors sous-optimale. Il a été observé néanmoins que ces zones correspondent à de forts rapports RSB, où le bruit de quantification est déjà probablement masqué par le signal utile.The best estimate of the RSB quantization signal-to-noise ratio is obtained for the low signal levels, ie when the RSB is low (and therefore when the noise is most audible). However, some segments have points well below the dashed line and the use of this simple rule is suboptimal. It has been observed, however, that these zones correspond to strong RSB ratios, where the quantization noise is already probably masked by the useful signal.
De manière générale, il a été observé que le traitement au sens de l'invention appliqué ici réalise néanmoins une réduction avantageuse du bruit de quantification.In general, it has been observed that the treatment according to the invention applied here nevertheless achieves an advantageous reduction of the quantization noise.
Dans le cas où la règle simple de l'équation (5) est utilisée, la
On a représenté sur la
On montre ainsi qu'une estimation très simple du rapport RSB reposant uniquement sur l'énergie du signal décodé peut donner de bons résultats pour un codage/décodage de type MICDA. L'estimation du rapport RSB peut être encore affinée en tenant compte par exemple du gain de prédiction des filtres ARMA (autorégressifs) qui interviennent dans le décodeur G.722.It is thus shown that a very simple estimate of the RSB ratio based solely on the energy of the decoded signal can give good results for ADPCM type coding / decoding. The estimation of the RSB ratio can be further refined by taking into account, for example, the prediction gain of the ARMA (autoregressive) filters which intervene in the G.722 decoder.
Connaissant la forme spectrale du bruit de quantification et son énergie, on peut efficacement appliquer le traitement de réduction de bruit de quantification de l'invention pour ce type de codage/décodage. Cet exemple est bien évidemment valable pour les autres types de codage/décodage de la même famille comme ceux normalisés G.726 ou G.727.Knowing the spectral shape of the quantization noise and its energy, the quantization noise reduction process of the invention can be effectively applied for this type of coding / decoding. This example is obviously valid for other types of coding / decoding of the same family as those standardized G.726 or G.727.
Bien entendu, la présente invention ne se limite pas à la forme de réalisation décrite ci-avant à titre d'exemple ; elle s'étend à d'autres variantes.Of course, the present invention is not limited to the embodiment described above by way of example; it extends to other variants.
Ainsi, il a été montré ci-avant qu'une application avantageuse de l'invention peut par exemple viser à réduire le bruit de quantification d'un codeur normalisé ITU-G.711 en utilisant les propriétés de la loi de quantification mise en oeuvre, en particulier selon la loi A en Europe. En effet, dans cette application, le bruit de quantification est blanc et il est possible d'estimer le rapport signal à bruit de quantification et, de là, une fonction de gain qui permette de réduire ce bruit. Une application avantageuse de l'invention vise alors la réduction de bruit de quantification dans le traitement à l'extension en bande élargie du codeur G.711 (ITU-T SG16, G.711WB).Thus, it has been shown above that an advantageous application of the invention can for example aim to reduce the quantization noise of a standardized ITU-G.711 encoder by using the properties of the quantization law implemented. , especially according to law A in Europe. Indeed, in this application, the quantization noise is white and it is possible to estimate the quantization signal-to-noise ratio and hence a gain function that makes it possible to reduce this noise. An advantageous application of the invention thus aims at the reduction of quantization noise in the processing at the extended band extension of the G.711 coder (ITU-T SG16, G.711WB).
Toutefois, le traitement du cas de la loi A a été donné ci-avant à titre d'exemple. De façon analogue, il aurait pu être décrit l'exemple de la loi µ (partie de la norme G.711 appliquée aux Etats-Unis).However, the treatment of the case of law A has been given above as an example. Similarly, it could have been described the example of the law μ (part of the G.711 standard applied in the United States).
Plus généralement, l'invention s'applique à tout type de codage/décodage dès lors que ses caractéristiques intrinsèques sont connues.More generally, the invention applies to any type of coding / decoding as long as its intrinsic characteristics are known.
Claims (8)
- Method for processing a digital audio signal,
said signal having been:- compression encoded (COD) according to a predetermined encoding type, applying a quantization operation,- then decoded (DEC),the processing method comprising:- an estimate (S4) of a quantization noise introduced by the compression encoding based on information (INF) obtained a priori on the type of compression encoding, and- a determination (S5) of a filtering function to be applied to the decoded signal in order to apply (S6) an estimated quantization noise reduction process (TBQ),characterized in that:- based on said information (INF), a variation (fig. 4) of the quantization noise (RSB) is estimated as a function of at least one parameter relative to a load parameter (Γ) of the decoded signal, and- according to a current value of said parameter (Γ) in the decoded signal (S52, S53), the quantization noise is estimated (S55; S56) in order to determine the filtering function (S57) to be applied (S58) to the decoded signal having said current parameter value (Γ). - Method according to Claim 1, characterized in that deduced from said a priori information is a variation model (fig. 4) of a signal-to-quantization noise ratio (RSB), as a function of said parameter (Γ) of the decoded signal.
- Method according to Claim 2, characterized in that a spectral coloration of the quantization noise is deduced from said a priori information and account is also taken of said spectral coloration in order to determine the filtering function to be applied to the decoded signal.
- Method according to one of Claims 1 to 3, characterized in that said a priori information is obtained during an encoder declaration procedure.
- Method according to one of Claims 1 to 4, characterized in that the compression encoding type is an encoding according to the G.711 standard.
- Device (TBQ) for processing a digital audio signal that is initially compression encoded according to a predetermined encoding type, then decoded, the processing device (TBQ) comprising:- means for estimating a quantization noise (BQ) introduced by the compression encoding, based on the decoded signal and information (INF) obtained a priori on the type of compression encoding, and- means for determining a filtering function to be applied to the decoded signal in order to apply (S6) an estimated quantization noise reduction process (FIL),characterized in that means for estimating estimate:- based on said information (INF), a variation (fig. 4) of the quantization noise (RSB) as a function of at least one parameter relative to a load parameter (Γ) of the decoded signal, and- according to a current value of said parameter (Γ) in the decoded signal (S52, S53), the quantization noise in order to determine the filtering function (S57) to be applied (S58) to the decoded signal having said current parameter value (Γ).
- Device according to Claim 6, characterized in that it is incorporated into a decoder, downstream of a decoding unit (DEC).
- Computer program, designed to be stored in the memory of a device (TBQ) for processing a digital audio signal that is initially compression encoded according to a predetermined encoding type, then decoded, characterized in that it comprises instructions for implementing the method according to one of Claims 1 to 5, when these instructions are executed by a processor of the processing device.
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PCT/FR2008/051057 WO2009004225A1 (en) | 2007-06-14 | 2008-06-13 | Post-processing for reducing quantification noise of an encoder during decoding |
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US8401845B2 (en) * | 2008-03-05 | 2013-03-19 | Voiceage Corporation | System and method for enhancing a decoded tonal sound signal |
JP5141633B2 (en) * | 2009-04-24 | 2013-02-13 | ソニー株式会社 | Image processing method and image information encoding apparatus using the same |
US8886523B2 (en) | 2010-04-14 | 2014-11-11 | Huawei Technologies Co., Ltd. | Audio decoding based on audio class with control code for post-processing modes |
JP5898515B2 (en) * | 2012-02-15 | 2016-04-06 | ルネサスエレクトロニクス株式会社 | Semiconductor device and voice communication device |
EP3537437B1 (en) * | 2013-03-04 | 2021-04-14 | VoiceAge EVS LLC | Device and method for reducing quantization noise in a time-domain decoder |
FR3007184A1 (en) * | 2013-06-14 | 2014-12-19 | France Telecom | MONITORING THE QUENTIFICATION NOISE ATTENUATION TREATMENT INTRODUCED BY COMPRESSIVE CODING |
JP5816992B2 (en) * | 2013-10-31 | 2015-11-18 | 株式会社アクセル | Filter design method and sound reproducing apparatus including the filter |
EP2887350B1 (en) * | 2013-12-19 | 2016-10-05 | Dolby Laboratories Licensing Corporation | Adaptive quantization noise filtering of decoded audio data |
US9881630B2 (en) * | 2015-12-30 | 2018-01-30 | Google Llc | Acoustic keystroke transient canceler for speech communication terminals using a semi-blind adaptive filter model |
JP2016105188A (en) * | 2016-01-12 | 2016-06-09 | 株式会社アクセル | Voice signal compression device and voice signal compression method |
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JPH0752844B2 (en) * | 1985-11-27 | 1995-06-05 | 日本電気株式会社 | Noise elimination circuit |
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JP3024468B2 (en) * | 1993-12-10 | 2000-03-21 | 日本電気株式会社 | Voice decoding device |
JP4358221B2 (en) * | 1997-12-08 | 2009-11-04 | 三菱電機株式会社 | Sound signal processing method and sound signal processing apparatus |
US6128346A (en) * | 1998-04-14 | 2000-10-03 | Motorola, Inc. | Method and apparatus for quantizing a signal in a digital system |
US6115689A (en) * | 1998-05-27 | 2000-09-05 | Microsoft Corporation | Scalable audio coder and decoder |
JP2000269821A (en) * | 1999-03-18 | 2000-09-29 | Oki Micro Design Co Ltd | Prediction encoding signal decoding device and noise removal method |
WO2003063160A1 (en) * | 2002-01-25 | 2003-07-31 | Koninklijke Philips Electronics N.V. | Method and unit for substracting quantization noise from a pcm signal |
US7328151B2 (en) * | 2002-03-22 | 2008-02-05 | Sound Id | Audio decoder with dynamic adjustment of signal modification |
KR100477699B1 (en) * | 2003-01-15 | 2005-03-18 | 삼성전자주식회사 | Quantization noise shaping method and apparatus |
US20060116874A1 (en) * | 2003-10-24 | 2006-06-01 | Jonas Samuelsson | Noise-dependent postfiltering |
CN1947407A (en) * | 2004-04-09 | 2007-04-11 | 日本电气株式会社 | Audio communication method and device |
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