CN107835422B - HEVC multi-description image coding algorithm based on significance - Google Patents

HEVC multi-description image coding algorithm based on significance Download PDF

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CN107835422B
CN107835422B CN201711033576.8A CN201711033576A CN107835422B CN 107835422 B CN107835422 B CN 107835422B CN 201711033576 A CN201711033576 A CN 201711033576A CN 107835422 B CN107835422 B CN 107835422B
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CN107835422A (en
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徐媛媛
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Hohai University HHU
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/136—Incoming video signal characteristics or properties
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/124—Quantisation
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
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    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/136—Incoming video signal characteristics or properties
    • H04N19/137—Motion inside a coding unit, e.g. average field, frame or block difference
    • H04N19/139—Analysis of motion vectors, e.g. their magnitude, direction, variance or reliability
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    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/174—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a slice, e.g. a line of blocks or a group of blocks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/176—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
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    • H04N19/463—Embedding additional information in the video signal during the compression process by compressing encoding parameters before transmission
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Abstract

The invention discloses a significance-based HEVC multi-description image coding algorithm, which comprises the following steps: HEVC intra-frame coding is carried out on the image by using a constant quantization step; the significance detection technology is adopted to carry out significance detection by utilizing HEVC coding characteristics, and the redundancy among descriptions is adjusted according to the detection result and the HEVC intra-frame coding is carried out for the second time; carrying out slice interleaving on the image slices subjected to twice encoding to generate two corresponding descriptions, wherein the two descriptions are transmitted in a network independently; at the receiving end, decoding is respectively carried out according to different situations that a single description is received or two descriptions are received simultaneously. The invention adopts multi-description technology to encode the image, so that the image required by the user can still be reconstructed under the condition of losing part of the description without requiring retransmission of lost data packets, and provides a robust image transmission scheme.

Description

HEVC multi-description image coding algorithm based on significance
Technical Field
The invention relates to the field of image communication, in particular to a significance-based HEVC multi-description image coding algorithm.
Background
With the development of smart phones and camera technologies, a large number of high-resolution images appear on various websites such as social networks and news media. The demand for image communication is also increasing. High resolution images present challenges to high quality image communication due to the dramatic increase in bit rate. In image communication, image coding is one of the core techniques that determine system performance. In recent years, the ISO/IEC moving Picture experts group and ITU-T video coding experts group jointly developed a new generation of high performance video coding (HEVC) standard, the extended range version of which can support the coding of still images.
Currently, the existing HEVC image coding method mainly focuses on improving compression performance and the like, and great progress has been made in these aspects. However, the following disadvantages still exist: (1) the existing HEVC image coding schemes do not take into account the robustness of image transmission. In a best-effort network such as the internet or an unreliable network such as a wireless ad hoc network, transmission of image signals may cause a serious packet loss due to a limited bandwidth and a poor network link quality. While the images are compressed, this effect may be further spread to the rest of the same image, causing a severe degradation of the image reconstruction quality. (2) With the existing HEVC image coding scheme, image data packets need to be retransmitted when severe loss of image data packets occurs. The retransmission may cause a large delay in image communication. If the data loss is caused by network congestion, the retransmission of the data packet will further aggravate the network congestion condition, resulting in more data packet loss. (3) The influence of each region of an image on the user experience cannot be fully considered in the existing HEVC coding scheme. The user is more sensitive to distortion of more prominent areas of the image and is more tolerant to distortion of less prominent areas.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a significance-based HEVC multi-description image coding algorithm, which can improve the robustness of image communication.
In order to solve the above technical problem, the present invention provides a significance-based HEVC multi-description image coding algorithm, including the following steps:
(1) HEVC intra-frame coding is carried out on the image by using a constant quantization step;
(2) the method comprises the steps of performing significance detection by using HEVC coding characteristics by adopting the existing significance detection technology, adjusting redundancy among descriptions according to a detection result, and performing HEVC intra-frame coding for the second time;
(3) carrying out slice interleaving on the image slices subjected to twice encoding to generate two corresponding descriptions, wherein the two descriptions are transmitted in a network independently; at the receiving end, decoding is respectively carried out according to different situations that a single description is received or two descriptions are received simultaneously.
Preferably, in step (1), the HEVC intra coding of the image using a constant quantization step is specifically: picture coding uses the coding tool slices provided by the HEVC standard, a picture is coded by being split into several slices,is marked as T1,T2,...,TNEach slice is a rectangular area which is self-contained in the image and can be independently decoded, a foundation is provided for later-stage slice interleaving and multi-description side path decoding, and the slice T is processed1,T2,...,TNThe corresponding quantization step is respectively marked as QP1,QP2,...,QPNThen, the quantization step size of the first HEVC coding can be represented by the following formula:
QP1＝QP2＝...＝QPN＝QPp，
wherein QPpThe quantization step used for the first encoding is represented as a fixed value.
Preferably, in step (2), the significance detection is performed by using the HEVC coding features by using the existing significance detection technology, and adjusting the redundancy between descriptions according to the detection result and performing the second HEVC intra-frame coding specifically include: averaging the significance characterizing values corresponding to all the coding units in each slice to obtain a significance characterizing value s of the slice1,s2,...,sNWherein 0 is ≤ siLess than or equal to 1; sheet TiCorresponding significance characterizing value siThe larger the value, the more easily the tile is noticed by the user, and the lower the user's tolerance to distortion of the tile; the redundancy between the two descriptions is adjusted according to the significance detection result, the second HEVC coding is coding for performing primary redundancy on all slices, the redundancy adjustment is to determine the quantization step size value of each slice of the second HEVC coding, and the significance characterization value is siSheet T ofiIts second coding quantization step QP'iCan be calculated by the following formula:
QP’i＝min((2-si)QPp,QPmax)，
wherein QPmaxQuantizing the maximum supported value of the step size for the encoder;
according to calculated QP'1，QP’2，...,QP’NHEVC coding for image for the second time by using corresponding quantization step size, wherein the significance represents value siQuantization step QP 'used by different slices'iAlso different; the significance characteristic value is 0-siAnd (3) being less than or equal to 1, wherein the relation between the second quantization step size and the first quantization step size is as follows:
QPp≤QP’i≤2*QPp.
the larger the quantization step size is, the worse the image block reconstruction quality is; in-sheet significance characterization value siIn the extreme case of 1, the second redundant encoding has the same image reconstruction quality as the first encoding; in most other cases, the picture restoration quality of the second redundant encoding is inferior to the restoration quality of the first encoding.
Preferably, in step (3), the image slices after two times of encoding are slice-interleaved to generate two corresponding descriptions, and the two descriptions are transmitted in the network independently; at the receiving end, decoding according to different situations of receiving a single description or simultaneously receiving two descriptions specifically includes: the process of slice interleaving is as follows: combining the code stream corresponding to the odd-numbered slice of the first HEVC intra-frame coding with the code stream corresponding to the even-numbered slice of the second HEVC redundant coding to generate description 1; and combining the code streams corresponding to the even number pieces of the first coding and the odd number pieces of the second coding together to generate a description 2, wherein the two descriptions are independent and can be transmitted in a network.
Preferably, at the decoding end, if only a single description is successfully received, side-path decoding is performed by the HEVC decoder; if only receiving the description 1, HEVC decoding is sequentially carried out on the description 1, high-quality image blocks of odd-numbered pieces and redundant image blocks of even-numbered pieces are recovered, the redundant image blocks are used for replacing lost high-quality image blocks of even-numbered pieces, and a rough image with acceptable quality is reconstructed; the side decoding process of description 2 is the same as that of description 1, and a reconstructed image with acceptable quality is obtained by decoding with an HEVC decoder.
Preferably, at the decoding end, if two descriptions are received simultaneously, decoding is performed by the central decoder; the central decoding process is as follows: HEVC decoding is sequentially performed on the description 1 and the description 2 respectively, high-quality image blocks capable of recovering odd-numbered slices and redundant image blocks capable of recovering even-numbered slices in the description 1, high-quality image blocks capable of recovering even-numbered slices and redundant image blocks capable of recovering odd-numbered slices in the description 2 are described, the redundant image blocks of the odd-numbered slices contained in the description 1 and the redundant image blocks of the even-numbered slices contained in the description 2 are discarded, and the high-quality image blocks of the odd-numbered slices and the high-quality image blocks of the even-numbered slices are combined to obtain a partial reconstructed image with better quality.
The invention has the beneficial effects that: the invention adopts multi-description technology to encode the image, so that the image required by the user can still be reconstructed under the condition of losing part of the description without requiring retransmission of lost data packets, and provides a robust image transmission scheme.
Drawings
Fig. 1 is an overall block diagram of a conventional multiple description coding communication system.
Fig. 2 is a schematic block diagram of the significance-based HEVC multiple description image coding algorithm according to the present invention.
FIG. 3 is a diagram of a slice interleaving link in multi-description coding according to the present invention.
Detailed Description
A significance-based HEVC multi-description image coding algorithm comprises the following steps:
(1) HEVC intra-frame coding is carried out on the image by using a constant quantization step;
(2) the method comprises the steps of performing significance detection by using HEVC coding characteristics by adopting the existing significance detection technology, adjusting redundancy among descriptions according to a detection result, and performing HEVC intra-frame coding for the second time;
(3) carrying out slice interleaving on the image slices subjected to twice encoding to generate two corresponding descriptions, wherein the two descriptions are transmitted in a network independently; at the receiving end, decoding is respectively carried out according to different situations that a single description is received or two descriptions are received simultaneously.
The overall block diagram of the multi-description image coding communication system adopted by the invention is shown in fig. 1, at a sending end, multi-description coding is carried out on an image to generate two independent descriptions, each description is independently transmitted in a network, the received description is decoded at a receiving end to obtain a reconstructed image signal, when the receiving end receives a single description, a side decoder is adopted to carry out decoding reconstruction, and when the two descriptions are received, a central decoder is adopted to carry out decoding reconstruction to recover the image.
The HEVC multiple description image coding algorithm based on significance proposed by the present invention is shown in fig. 2, and includes the following steps:
step one, performing first HEVC intra-frame coding on an image by using a constant quantization step size.
This picture coding uses the coding tools-slices (tiles) provided by the HEVC standard. An image is divided into several slices for coding, which can be denoted as T1,T2,...,TN. Each slice is a self-contained and independently decodable rectangular region of a block in the picture, which provides a basis for later slice interleaving, multi-description side-way decoding. Will slice T1,T2,...,TNThe corresponding quantization step is respectively marked as QP1,QP2,...,QPNThen, the quantization step size of the first HEVC coding can be represented by the following formula:
QP1＝QP2＝...＝QPN＝QPp，
wherein QPpThe quantization step used for the first encoding is represented as a fixed value.
And step two, the existing significance detection technology is adopted to carry out significance detection by utilizing HEVC coding characteristics, and redundancy among descriptions is adjusted according to the detection result and second HEVC intra-frame coding is carried out.
The purpose of image saliency detection is to effectively predict the degree of attention allocation of human beings to different regions of an image. The invention adopts the prior art to detect the significance of the image. The technology utilizes three feature information of a coding unit after HEVC coding, namely, the dividing depth, the bit rate distribution and the motion vector to obtain the significance information of each coding unit.
The significance characterizing values corresponding to all coding units in each slice are averaged to obtain the significance characterizing value s of the slice1,s2,...,sNWherein 0 is ≤ siLess than or equal to 1. Sheet TiCorresponding significance characterizing value siThe larger the value, the more noticeable the tile is to the user, and the less tolerant the user is to distortion of the tile.
The redundancy between the two descriptions in the scheme will be adjusted according to the significance test results. The second HEVC coding is coding in which redundancy is performed on all slices again, and the redundancy adjustment is to determine the quantization step size value of each slice of the second HEVC coding. Characterization value for significance is siSheet T ofiIts second coding quantization step QPi' can be calculated from the following equation:
QP’i＝min((2-si)QPp,QPmax)，
wherein QPmaxThe maximum supported value of the step size is quantized for the encoder.
According to calculated QP'1，QP’2，...,QP’NAnd carrying out HEVC coding on the image for the second time by using the corresponding quantization step. Significance characterizing value siQuantization step QP 'used by different slices'iAnd also different. The significance characteristic value is 0-siAnd (3) being less than or equal to 1, wherein the relation between the second quantization step size and the first quantization step size is as follows:
QPp≤QP’i≤2*QPp.
the larger the quantization step size, the worse the image block reconstruction quality. In-sheet significance characterization value siIn the extreme case of 1, the second redundant encoding has the same image reconstruction quality as the first encoding; in most other cases, the picture restoration quality of the second redundant encoding is inferior to the restoration quality of the first encoding.
And step three, carrying out slice interleaving on the image slices subjected to twice encoding to generate two corresponding descriptions, wherein the two descriptions are transmitted in the network independently.
Finally, two independent equalized descriptions are generated through chip interleaving. As shown in fig. 3, the process of slice interleaving is as follows: combining the code stream corresponding to the odd-numbered slice of the first HEVC intra-frame coding with the code stream corresponding to the even-numbered slice of the second HEVC redundant coding to generate description 1; and combining the code streams corresponding to the even number pieces of the first coding and the odd number pieces of the second coding together to generate description 2. The two descriptions are transmitted independently in the network.
At the decoding end, if only a single description is successfully received, side-path decoding is performed by the HEVC decoder. In the side-road decoding process, by taking only the description 1 as an example, HEVC decoding is sequentially performed on the description 1, so that high-quality image blocks of odd-numbered pieces and redundant image blocks of even-numbered pieces can be recovered, and the lost high-quality image blocks of even-numbered pieces are replaced by the redundant image blocks, so that a rough image with acceptable quality can be reconstructed; the side decoding process of description 2 is the same as that of description 1, and a reconstructed image with acceptable quality is obtained by decoding with an HEVC decoder.
At the decoding end, if both descriptions are received simultaneously, decoding is performed by the central decoder. The central decoding process is as follows: HEVC decoding is sequentially performed on the description 1 and the description 2 respectively, a high-quality image block capable of recovering an odd slice and a redundant image block capable of recovering an even slice in the description 1, a high-quality image block capable of recovering an even slice and a redundant image block capable of recovering an odd slice in the description 2, the redundant image block of the odd slice contained in the description 1 and the redundant image block of the even slice contained in the description 2 are discarded, and the high-quality image blocks of the odd slice and the even slice are combined to obtain a partial reconstruction image with better quality.
According to the method, the image is subjected to HEVC coding, the characteristics after HEVC coding are subjected to significance analysis, redundancy adjustment and redundancy coding are performed according to the characteristics, and then slice interleaving is performed to generate a plurality of descriptions. Compared with the conventional HEVC image coding scheme which only generates one code stream, the multi-description image coding scheme can achieve better reconstructed image quality in an unreliable network. Because each description can be independently decoded to recover the image signal, when one described data packet is lost, the lost data packet does not need to be retransmitted, and the other description can be used for decoding, so that the real-time communication requirement can be met, and the network congestion can be reduced compared with a scheme of retransmitting the data packet. Meanwhile, as the redundancy among the descriptions is adjusted according to the significance, the visual experience of the user under the same network condition is better.
While the invention has been shown and described with respect to the preferred embodiments, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the scope of the invention as defined in the following claims.

Claims (4)

1. An HEVC multi-description image coding algorithm based on significance is characterized by comprising the following steps:
(1) HEVC intra-frame coding is carried out on the image by using a constant quantization step; the method specifically comprises the following steps: the image coding uses the coding tool slice provided by HEVC standard, and an image is divided into a plurality of slices for coding, and the T is marked1,T2,...,TNEach slice is a rectangular area which is self-contained in the image and can be independently decoded, a foundation is provided for later-stage slice interleaving and multi-description side path decoding, and the slice T is processed1,T2,...,TNThe corresponding quantization step is respectively marked as QP1,QP2,...,QPNThen, the quantization step size of the first HEVC coding can be represented by the following formula:
QP1＝QP2＝...＝QPN＝QPp，
wherein QPpThe quantization step used for the first encoding is represented as a fixed value;
(2) the method comprises the steps of performing significance detection by using HEVC coding characteristics by adopting a significance detection technology, adjusting redundancy among descriptions according to a detection result, and performing HEVC intra-frame coding on an original image for the second time;
(3) carrying out slice interleaving on the image slices subjected to twice encoding to generate two corresponding descriptions, wherein the two descriptions are transmitted in a network independently; at a receiving end, decoding is respectively carried out according to different conditions of receiving a single description or simultaneously receiving two descriptions; the process of slice interleaving is as follows: combining the code stream corresponding to the odd-numbered slice of the first HEVC intra-frame coding with the code stream corresponding to the even-numbered slice of the second HEVC redundant coding to generate description 1; and combining the code streams corresponding to the even number pieces of the first coding and the odd number pieces of the second coding together to generate a description 2, wherein the two descriptions are independent and can be transmitted in a network.
2. The HEVC multi-description image coding algorithm based on significance as claimed in claim 1, wherein in step (2), the significance detection is performed by using the HEVC coding features using the existing significance detection technique, and the adjusting the redundancy between descriptions according to the detection result and performing the second HEVC intra-coding specifically comprises: averaging the significance characterizing values corresponding to all the coding units in each slice to obtain a significance characterizing value s of the slice1,s2,...,sNWherein 0 is ≤ siLess than or equal to 1; sheet TiCorresponding significance characterizing value siThe larger the value, the more easily the tile is noticed by the user, and the lower the user's tolerance to distortion of the tile; the redundancy between the two descriptions is adjusted according to the significance detection result, the second HEVC coding is coding for performing primary redundancy on all slices, the redundancy adjustment is to determine the quantization step size value of each slice of the second HEVC coding, and the significance characterization value is siSheet T ofiIts second coding quantization step QP'iCan be calculated by the following formula:
QP’i＝min((2-si)QPp,QPmax)，
wherein QPmaxQuantizing the maximum supported value of the step size for the encoder;
according to calculated QP'1，QP’2，...,QP’NHEVC coding for image for the second time by using corresponding quantization step size, wherein the significance represents value siQuantization step QP 'used by different slices'iAlso different; the significance characteristic value is 0-siAnd (3) being less than or equal to 1, wherein the relation between the second quantization step size and the first quantization step size is as follows:
QPp≤QP’i≤2*QPp.
the larger the quantization step size is, the worse the image block reconstruction quality is; in-sheet significance characterization value siIn the extreme case of 1, the second redundant encoding has the same image reconstruction quality as the first encoding; in most other cases, secondThe picture restoration quality of the secondary redundant encoding is inferior to that of the first encoding.
3. The significance-based HEVC multi-description image coding algorithm of claim 1, wherein at the decoding end, if only a single description is successfully received, edge decoding is performed by an HEVC decoder; if only receiving the description 1, HEVC decoding is sequentially carried out on the description 1, high-quality image blocks of odd-numbered pieces and redundant image blocks of even-numbered pieces are recovered, the redundant image blocks are used for replacing lost high-quality image blocks of even-numbered pieces, and a rough image with acceptable quality is reconstructed; the side decoding process of description 2 is the same as that of description 1, and a reconstructed image with acceptable quality is obtained by decoding with an HEVC decoder.
4. HEVC multiple description image coding algorithm based on saliency as claimed in claim 1 characterized in that at the decoding end, if two descriptions are received simultaneously, the decoding is performed by a central decoder; the central decoding process is as follows: HEVC decoding is sequentially performed on the description 1 and the description 2 respectively, high-quality image blocks capable of recovering odd-numbered slices and redundant image blocks capable of recovering even-numbered slices in the description 1, high-quality image blocks capable of recovering even-numbered slices and redundant image blocks capable of recovering odd-numbered slices in the description 2 are described, the redundant image blocks of the odd-numbered slices contained in the description 1 and the redundant image blocks of the even-numbered slices contained in the description 2 are discarded, and the high-quality image blocks of the odd-numbered slices and the high-quality image blocks of the even-numbered slices are combined to obtain a partial reconstructed image with better quality.
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