CN105611289B - Low-resolution image coding method based on intelligent quantization technology - Google Patents

Low-resolution image coding method based on intelligent quantization technology Download PDF

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CN105611289B
CN105611289B CN201511005039.3A CN201511005039A CN105611289B CN 105611289 B CN105611289 B CN 105611289B CN 201511005039 A CN201511005039 A CN 201511005039A CN 105611289 B CN105611289 B CN 105611289B
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CN105611289A (en
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朱树元
曾辽原
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University of Electronic Science and Technology of China
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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
    • H04N19/146—Data rate or code amount at the encoder output
    • 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
    • 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
    • H04N19/164—Feedback from the receiver or from the transmission channel
    • H04N19/166—Feedback from the receiver or from the transmission channel concerning the amount of transmission errors, e.g. bit error rate [BER]

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Abstract

The present invention provides a kind of low-resolution image coding methods based on intelligent quantization technology, it is to carry out rational coding resource distribution by intelligent quantization technology, distinguishing coding and rebuilding is carried out to the pixel in image using intelligent quantization technology, the pixel that display exports is needed to carry out high quality compressed encoding, pixel to that need not carry out display output carries out low quality compressed encoding, adapts to the low resolved reconstruction demand of efficient image after coding.Compared with the implementation method of traditional " coding compression+low resolution is shown " based on jpeg image coding standard, the present invention can show the specific requirements of output according to low resolution, neatly allocated code resource, to improve the coding quality of output pixel point, overcome conventional method be difficult to control pixel coding quality the shortcomings that.

Description

Low-resolution image coding method based on intelligent quantization technology
Technical field
The invention belongs to image code domains, relate generally to the compress technique of digital picture.
Background technology
With the development of multimedia technology, it is desirable that the coding compression of image will not only meet changeable transmission conditions, but also Different display environments is adapted to, especially for the picture signal taken, it would be desirable to be able to which adaptation includes smart mobile phone and tablet The various demands for being only equipped with low resolution and showing the playback terminal of screen including computer.Therefore, how to picture signal Taken into account during coding compression efficient low resolution and show demand, it is one big to be that current image code domain is faced Challenge.
The low resolution of image is shown, the down-sampling in spatial domain is typically carried out to picture signal, reduces the picture shown by it Vegetarian refreshments is to meet the requirement of low point of reduction resolution ratio.In current practical application, it is necessary first to be carried out to original image signal Coding compression, then again carries out compressed image the down-sampling in spatial domain, then could carry out the display of low resolution.Tradition The implementation method of " coding compression+low resolution show " be first with the method based on jpeg image coding standard to image Interior all pixels point such as carries out at the compression of quality, then the side only to needing partial pixel point to be shown to pass through spatial domain down-sampling Formula carries out low resolution display output.After such realization step, the mistake of pixel after most of coding in down-sampling Journey is dropped without being used, therefore causes the waste of coding resource, is resulted in and is rebuild to compression image low resolution Inefficiency, referring to bibliography " JPEG (Joint Photographic Experts Group):ISO/IEC IS 10918–1/ITU-T Recommendation T.81,Digital Compression and Coding of Continuous-Tone Still Image,1993”.If capableing of the resource of reasonable distribution coding, to needing to carry out low resolution The pixel of rate display output carries out high quality coding, and the pixel to that need not carry out display output carries out low quality coding, The whole efficiency that the low resolution of compression image is rebuild will so be greatlyd improve.
Invention content
The object of the present invention is to provide a kind of novel low-resolution image coding method based on intelligent quantization technology, this Kind of method mainly carries out rational coding resource distribution using intelligent quantization technology, improve in an encoding process partly need into The quality of the pixel of row display output, to adapt to the low resolved reconstruction demand of efficient image after coding.With it is traditional based on The implementation method of " coding compression+low resolution is shown " of jpeg image coding standard is compared, and the present invention can be according to low resolution Rate shows the specific requirements of output, and neatly allocated code resource overcomes tradition to improve the coding quality of output pixel point Method is unable to control the shortcomings that pixel coding quality.
In order to facilitate description present disclosure, following term definition is done first：
1 is defined, the method for image block in traditional jpeg image compression standard
Original image is divided by traditional image block method according to the method for carrying out piecemeal to image in Joint Photographic Experts Group The equidimension image block of multiple non-overlapping copies specifically describes process referring to " JPEG (Joint Photographic Experts Group):ISO/IEC IS 10918–1/ITU-T Recommendation T.81,Digital Compression and Coding of Continuous-Tone Still Image,1993”；
2 are defined, traditional encryption algorithm based on intelligent quantization technology
Traditional encryption algorithm based on intelligent quantization technology can be as needed to the partial pixel in each image block Point carries out the compression of high quality, and low-quality compression is carried out to remaining pixel.This method will carry out the picture of high quality compression The coordinated indexing set of vegetarian refreshments is defined as Ω1, the coordinated indexing set for the pixel for carrying out low quality compression is defined as Ω2；And Transform domain by transformation coefficient be divided into two groups commonly quantified respectively and pressure type quantify, the transformation series that will be commonly quantified Several coordinated indexing set are defined as Ψ1, the coordinated indexing set for the transformation coefficient for carrying out pressure type quantization is defined as Ψ2；Together When, three kinds of classical quantization strategies, i.e. quantization strategy -1, quantization strategy -2 and amount are provided in traditional intelligent quantization technology Change strategy -3, selection when as quantization；Wherein, after the Partial Transformation coefficient pressure after transformation is quantified as 0 by quantization strategy -1, Remaining quantization parameter is adjusted again；Quantization strategy -2 uses the quantization method quantized segment in traditional jpeg image compression standard After transformation coefficient, then adjust remaining quantization parameter；Quantization strategy -3 uses the quantization in traditional jpeg image compression standard After method quantized segment transformation coefficient, then adjust remaining non-zero quantized coefficients.For the image block of input, this method can be into The number of coded bits of image after row coding and decoding and calculation code；Specific descriptions process is referring to document " Constrained quantization in the transform domain with applications in arbitrarily-shaped object coding”；
3 are defined, traditional bicubic interpolation method
Traditional bicubic interpolation method is most common interpolation method in two-dimensional space, in this interpolation method, point Value at (u, v) can be obtained by the weighted average of 16 points nearest in rectangular mesh around it；Specific descriptions process Referring to document " Cubic convolution interpolation for digital image processing "；
4 are defined, the method for image block composograph in traditional jpeg image compression standard
The method of traditional image block composograph is carried out mutually not with image block according in jpeg image compression standard Method of the overlapping combinations to synthesize complete image specifically describes process referring to " JPEG (Joint Photographic Experts Group):ISO/IEC IS 10918–1/ITU-T Recommendation T.81,Digital Compression and Coding of Continuous-Tone Still Image,1993”；
Step 1, the pretreatment of image
By the input picture that size is W × H, divided according to the method for image block in traditional jpeg image compression standard For N=(W × H)/82A non-overlapping copies, the square image blocks that size is 8 × 8 are denoted as B1, B2..., Bi..., BN, here, The width of W representative images, the height of H representative images, the total number of image block, the rope of i representative image blocks after N representative images divide Draw, i ∈ { 1,2 ..., N }；
Step 2, the image block coding parameter setting based on intelligent quantization technology
First, using the quantization strategy -1 provided in traditional encryption algorithm based on intelligent quantization technology；
Secondly, the pixel for needing to carry out high quality compression in traditional encryption algorithm based on intelligent quantization technology is defined Coordinated indexing collection is combined intoIt defines and needs to carry out low quality compression in traditional encryption algorithm based on intelligent quantization technology The coordinated indexing collection of pixel is combined intoHere,It is one 1 × 16 row vector, It is one 1 × 48 row vector,
Finally, it defines in traditional encryption algorithm based on intelligent quantization technology and needs the transformation coefficient commonly quantified Coordinated indexing collection be combined intoIt defines and needs to carry out pressure type quantization in traditional encryption algorithm based on intelligent quantization technology The coordinated indexing collection of transformation coefficient be combined intoHere,It is one 1 × 16 row vector, It is one 1 × 48 row vector,
Step 3, the tile compression based on intelligent quantization technology
The image block B for being 8 × 8 firstly, for generated size in step 1i, using traditional based on intelligent quantization skill The image block coding parameter being arranged in the encryption algorithm and step 2 of art is coded and decoded, obtain that treated image block, note For B 'i,
Here, β 'm,nIt is B 'iIn element, m represents B 'iThe abscissa of interior element, n represent B 'iThe ordinate of interior element, m It is natural number, 1≤m≤8,1≤n≤8 with n；The index of i representative image blocks, i ∈ { 1,2 ..., N }, N represent image in step 1 The total number of image block after division；
Then, using traditional bicubic interpolation method to B 'iIn be located at pixel on the position (u, v) into row interpolation, Here, u is B 'iThe abscissa of interior pixel, v are B 'iThe ordinate of interior pixel, u and v are natural numbers, 1≤u≤8,1≤v≤ 8, and be odd number when u with v differences；Image block is obtained after interpolation, is denoted as
Here,It isIn element, m representThe abscissa of interior element, n are representedThe ordinate of interior element, m and N is natural number, 1≤m≤8,1≤n≤8；The index of i representative image blocks, i ∈ { 1,2 ..., N }, N represent image in step 1 and draw The total number of image block after point；
Step 4, spatial domain down-sampling
First, the full null graph that one size of definition is 4 × 4 is denoted as b as block matrixi：
Here, the index of i representative images block, i ∈ { 1,2 ..., N }, N represent the total of image block after image in step 1 divides Number；
Then, matrix step 3 obtainedIn elementWithIt takes out one by one, is sequentially placed into bi The 1st row；It willIn elementWithIt takes out one by one, is sequentially placed into biThe 2nd row；It willIn element WithIt takes out one by one, is sequentially placed into biThe 3rd row；It willIn elementWithBy A taking-up, is sequentially placed into biThe 4th row；Obtain image block b 'i：
Here,It isIn element, m representThe abscissa of interior element, n are representedThe ordinate of interior element, m and N is odd number, and 1≤m≤8,1≤n≤8；The index of i representative image blocks, i ∈ { 1,2 ..., N }, N, which is represented in step 1, to scheme As the total number of image block after dividing；
Step 5, high-definition picture is built
For the image block generated in step 3Using image block composograph in traditional jpeg image compression standard Method, generate size be W × H image, be denoted asHere, W represents the width of input picture in step 1, and H represents step 1 The height of middle input picture, the index of i representative image blocks, i ∈ { 1,2 ..., N }, N represent in step 1 image block after image divides Total number.
Step 6, low-resolution image is built
For the image block b ' generated in step 4i, using image block composograph in traditional jpeg image compression standard Method, generate size be (W/2) × (H/2) image, be denoted asHere, W represents the width of input picture in step 1, H generations The height of input picture in table step 1, the index of i representative image blocks, i ∈ { 1,2 ..., N }, N represent image in step 1 and divide The total number of image block afterwards.
The basic principle of the present invention：Using intelligent quantization technology distinguishing coding can be carried out to the pixel in image It rebuilds, high quality coding is carried out to the partial pixel point of encoded images, low quality coding is carried out to another part pixel, and And it can effectively reduce whole encoder bit rate.When carrying out low resolution reconstruction to compressed image, intelligence can be utilized Quantification technique is to needing to show that the pixel of output carries out high quality compressed encoding, to that need not carry out the pixel of display output Low quality compressed encoding is carried out, had not only improved the quality of low resolution coded image in this way, but also reduce the code check of coding, is realized Efficient coding compression and low resolution display output.
The present invention essence be：High quality low resolution in order to meet compressed images shows demand, will be based on intelligence The coding method of quantification technique is applied in image coding, by reasonable distribution coding resource, to constituting low resolution output figure High quality coding is carried out in the region of picture, and low quality coding is carried out in the region that other need not be carried out with display output.
The innovative point of the present invention：It, will during the present invention shows intelligent quantization technology applied to the low resolution of compression image Image encodes and low resolution reconstruction is combined, and realizes efficient compression image low resolution display output.
Advantages of the present invention:Realize coding compression and the combination that shows of various resolution ratio of image, image it is compressed Journey shows for high quality low resolution provides powerful guarantee.The present invention is carrying out coding compression to original high-resolution image Afterwards, the low-resolution image that can export the preferable high-definition picture of visual effect and outputting high quality, meets different Display demand.
Description of the drawings
Fig. 1 is the implementation process of the present invention；
Fig. 2 is the PSNR values obtained under identical encoder bit rate using different images coding method.
Specific implementation mode
The present invention mainly verifies the feasibility of the system model by the way of emulation experiment, and all steps are all by experiment Verification, to realize that the compression of images based on transform domain down-sampling technology, specific implementation step are as follows：
Step 1, the pretreatment of image
Set the width W=8 of imagem, the height H=8 of imagen, m and n is natural number here, according to traditional JPEG The method of image block is divided into N=(W × H)/8 in Standard of image compression2A non-overlapping copies, the square that size is 8 × 8 Image block is denoted as B1, B2..., Bi..., BN, here, the width of W representative images, the height of H representative images, N representative images stroke The total number of image block, the index of i representative image blocks, i ∈ { 1,2 ..., N } after point；
Step 2, the image block coding parameter setting based on intelligent quantization technology
First, using the quantization strategy -1 provided in traditional encryption algorithm based on intelligent quantization technology；
Secondly, the pixel for needing to carry out high quality compression in traditional encryption algorithm based on intelligent quantization technology is defined Coordinated indexing collection is combined intoIt defines and needs to carry out low quality compression in traditional encryption algorithm based on intelligent quantization technology The coordinated indexing collection of pixel is combined intoHere,It is one 1 × 16 row vector, It is one 1 × 48 row vector,
Finally, it defines in traditional encryption algorithm based on intelligent quantization technology and needs the transformation coefficient commonly quantified Coordinated indexing collection is combined intoDefine the change for needing to carry out pressure type quantization in traditional encryption algorithm based on intelligent quantization technology The coordinated indexing collection for changing coefficient is combined intoHere,It is one 1 × 16 row vector, It is one 1 × 48 row vector,
Step 3, the tile compression based on intelligent quantization technology
The image block B for being 8 × 8 firstly, for generated size in step 1i, using traditional based on intelligent quantization skill The image block coding parameter being arranged in the encryption algorithm and step 2 of art is coded and decoded, obtain that treated image block, note For B 'i,
Here, β 'm,nIt is B 'iIn element, m represents B 'iThe abscissa of interior element, n represent B 'iThe ordinate of interior element, m It is natural number, 1≤m≤8,1≤n≤8 with n；The index of i representative image blocks, i ∈ { 1,2 ..., N }, N represent image in step 1 The total number of image block after division；
Then, using traditional bicubic interpolation method to B 'iIn be located at pixel on the position (u, v) into row interpolation, Here, u is B 'iThe abscissa of interior pixel, v are B 'iThe ordinate of interior pixel, u and v are natural numbers, 1≤u≤8,1≤v≤ 8, and be odd number when u with v differences；Image block is obtained after interpolation, is denoted as
Here,It isIn element, m representThe abscissa of interior element, n are representedThe ordinate of interior element, m and N is natural number, 1≤m≤8,1≤n≤8；The index of i representative image blocks, i ∈ { 1,2 ..., N }, N represent image in step 1 and draw The total number of image block after point；
Step 4, spatial domain down-sampling
First, the full null graph that one size of definition is 4 × 4 is denoted as b as block matrixi：
Here, the index of i representative images block, i ∈ { 1,2 ..., N }, N represent the total of image block after image in step 1 divides Number；
Then, matrix step 3 obtainedIn elementWithIt takes out one by one, is sequentially placed into bi The 1st row；It willIn elementWithIt takes out one by one, is sequentially placed into biThe 2nd row；It willIn element WithIt takes out one by one, is sequentially placed into biThe 3rd row；It willIn elementWithBy A taking-up, is sequentially placed into biThe 4th row；Obtain image block b 'i：
Here,It isIn element, m representThe abscissa of interior element, n are representedThe ordinate of interior element, m and N is odd number, and 1≤m≤8,1≤n≤8；The index of i representative image blocks, i ∈ { 1,2 ..., N }, N, which is represented in step 1, to scheme As the total number of image block after dividing；
Step 5, high-definition picture is built
For the image block generated in step 3Using image block composograph in traditional jpeg image compression standard Method, generate size be W × H image, be denoted asHere, W represents the width of input picture in step 1, and H represents step 1 The height of middle input picture, the index of i representative image blocks, i ∈ { 1,2 ..., N }, N represent in step 1 image block after image divides Total number.
Step 6, low-resolution image is built
For the image block b ' generated in step 4i, using image block composograph in traditional jpeg image compression standard Method, generate size be (W/2) × (H/2) image, be denoted asHere, W represents the width of input picture in step 1, H generations The height of input picture in table step 1, the index of i representative image blocks, i ∈ { 1,2 ..., N }, N represent image in step 1 and divide The total number of image block afterwards.
Embodiment is applied in the classical legend that Lena and two width resolution ratio of Barbara are 512 × 512, attached drawing 2 be Under different encoder bit rates, the peak value obtained after being coded and decoded using different method for compressing image to different images is believed It makes an uproar than (peak signal to noise ratio, PSNR).It is obvious that the method in the present invention has significantly than existing methods Performance boost.

Claims (1)

1. a kind of low-resolution image coding method based on intelligent quantization technology, it is characterized in that it includes the following steps：
Step 1, the pretreatment of image
By the input picture that size is W × H, N is divided into according to the method for image block in traditional jpeg image compression standard =(W × H)/82A non-overlapping copies, the square image blocks that size is 8 × 8 are denoted as B1, B2..., Bi..., BN, here, W generations The width of table image, the height of H representative images, the total number of image block after N representative images divide, the index of i representative image blocks, I ∈ { 1,2 ..., N }；
Step 2, the image block coding parameter setting based on intelligent quantization technology
First, using the quantization strategy provided in traditional encryption algorithm based on intelligent quantization technology, here, the quantization plan Slightly refer to forcing the Partial Transformation coefficient after transformation after being quantified as 0, then adjust the quantization strategy of remaining quantization parameter；
Secondly, the seat for the pixel for needing to carry out high quality compression in traditional encryption algorithm based on intelligent quantization technology is defined Mark indexed set is combined intoDefine the picture for needing to carry out low quality compression in traditional encryption algorithm based on intelligent quantization technology The coordinated indexing collection of vegetarian refreshments is combined intoHere,It is one 1 × 16 row vector, It is one 1 × 48 row vector,
Finally, the seat that the transformation coefficient commonly quantified is needed in traditional encryption algorithm based on intelligent quantization technology is defined Mark indexed set is combined intoDefine the change for needing to carry out pressure type quantization in traditional encryption algorithm based on intelligent quantization technology The coordinated indexing collection for changing coefficient is combined intoHere,It is one 1 × 16 row vector, It is one 1 × 48 row vector,
Step 3, the tile compression based on intelligent quantization technology
The image block B for being 8 × 8 firstly, for generated size in step 1i, joined according to the image block coding being arranged in step 2 Number, is coded and decoded using traditional encoding and decoding algorithm based on intelligent quantization technology, obtain that treated image block, note For B 'i,
Here, β 'm,nIt is B 'iIn element, m represents B 'iThe abscissa of interior element, n represent B 'iThe ordinate of interior element, m and n It is natural number, 1≤m≤8,1≤n≤8；The index of i representative image blocks, i ∈ { 1,2 ..., N }, N represent image in step 1 and divide The total number of image block afterwards；
Then, using traditional bicubic interpolation method to B 'iIn be located at pixel on the position (u, v) into row interpolation, here, u For B 'iThe abscissa of interior pixel, v are B 'iThe ordinate of interior pixel, u and v are natural numbers, 1≤u≤8,1≤v≤8, and It is odd number when u with v differences；Image block is obtained after interpolation, is denoted as
Here,It isIn element, m representThe abscissa of interior element, n are representedThe ordinate of interior element, m and n are Natural number, 1≤m≤8,1≤n≤8；The index of i representative image blocks, i ∈ { 1,2 ..., N }, N are represented in step 1 after image division The total number of image block；
Step 4, spatial domain down-sampling
First, the full null graph that one size of definition is 4 × 4 is denoted as b as block matrixi：
Here, the index of i representative images block, i ∈ { 1,2 ..., N }, N represent total of image block after image in step 1 divides Number；
Then, matrix step 3 obtainedIn elementWithIt takes out one by one, is sequentially placed into biThe 1st Row；It willIn elementWithIt takes out one by one, is sequentially placed into biThe 2nd row；It willIn element WithIt takes out one by one, is sequentially placed into biThe 3rd row；It willIn elementWithIt takes one by one Go out, is sequentially placed into biThe 4th row；Obtain image block b 'i：
Here,It isIn element, m representThe abscissa of interior element, n are representedThe ordinate of interior element, m and n are Odd number, and 1≤m≤8,1≤n≤8；The index of i representative image blocks, i ∈ { 1,2 ..., N }, N represent image in step 1 and divide The total number of image block afterwards；
Step 5, high-definition picture is built
For the image block generated in step 3Using the side of image block composograph in traditional jpeg image compression standard Method generates the image that size is W × H, is denoted asHere, W represents the width of input picture in step 1, and H represents defeated in step 1 Enter the height of image, the index of i representative image blocks, i ∈ { 1,2 ..., N }, N represent the total of image block after image divides in step 1 Number；
Step 6, low-resolution image is built
For the image block b ' generated in step 4i, using the side of image block composograph in traditional jpeg image compression standard Method generates the image that size is (W/2) × (H/2), is denoted asHere, W represents the width of input picture in step 1, H ride instead of walk The height of input picture in rapid 1, the index of i representative image blocks, i ∈ { 1,2 ..., N }, N represent image in step 1 to scheme after dividing As the total number of block.
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CN104935928A (en) * 2015-06-01 2015-09-23 电子科技大学 High-efficiency image compression method based on spatial domain downsampling mode

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JPH09275561A (en) * 1996-04-08 1997-10-21 Toshiba Corp Video compressor and video compression method
JPH10341369A (en) * 1997-06-10 1998-12-22 Eastman Kodak Japan Kk Electronic image-pickup device
CN103475876A (en) * 2013-08-27 2013-12-25 北京工业大学 Learning-based low-bit-rate compression image super-resolution reconstruction method
CN104867165A (en) * 2015-05-19 2015-08-26 电子科技大学 Cramping method based on sampling technology under transform domain
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