Video encoding and decoding method based on three-dimensional discrete cosine transform

FIELD: physics.

SUBSTANCE: adaptation is performed by rearranging fragments of discrete cosine transform (DCT) coefficients obtained after two-dimensional DCT on the time axis and subsequent one-dimensional DCT such that the total number of non-zero transform coefficients after three-dimensional DCT is less than the number of non-zero DCT coefficients obtained after three-dimensional DCT without rearranging two-dimensional DCT fragments. In the disclosed method, after forming a domain measuring n×n×n pixels, DCT coefficients are calculated on spatial coordinates x and y for each fragment of the domain. The fragments are then rearranged in the form of a rearrangement vector and a time DCT operation is performed. The DCT coefficients are sampled, encoded and transmitted over a communication channel with the rearrangement vector. At reception, said procedures are performed in reverse order and the original video stream is restored.

EFFECT: high degree of compression of video data with a given image reconstruction error at reception owing to adaptation to variation of static properties of images.

3 cl, 9 dwg

 

The invention relates to the field of encoding, namely to a method for the compression of moving images to reduce the amount of data needed for storage or transmitted over the communication channel for subsequent reconstruction of images at the reception.

A method of coding based on three-dimensional discrete cosine transform (DCT) [R. Zaharia, A. Aggoun, M. McCormick Adaptive 3D-DCT compression algorithm for continuous parallax 3D integral imaging. Journal of Signal processing: Image Communication. 17, pp. 231-242, 2002].

The disadvantage of this method is the lack of adaptation in the encoding process to the degree of mobility of the movable frame image, which increases the amount of data on the output of the encoder at a given coding error.

A method of compressing video data using three-dimensional DCT (DCT-3) [N. Bozinovic, Konrad J. Scan or derandquantization for 3D-DCT coding in Proc. of SPIEV is. Comm. Andlm. Proc. Vol.5150. pp. 1204-1215, 2003].

This method applies processing frames of the video sequence based on the three-dimensional DCT. The operation transformation starts with the spatial coordinates x and y, and the resulting spectral coefficients of the two-dimensional DCT (DCT-2) are subjected to one-dimensional DCT (DCT-1) on the time coordinate t to reduce temporal redundancy.

The main disadvantage of analogue is the lack of adaptability of encoding operations to stat�stick to the original picture which leads to the impossibility of achieving high compression ratios.

The closest in technical essence to the claimed method is a Method of encoding and decoding video data based on three-dimensional discrete cosine transform", patent RU No. 2375838, publ. 10.12.2009, bull. No. 34. Prototype method consists in the following steps: on transmission of a sequence of television frames break packages for n frames, which form the domains of size n×n×n pixels, then the first phase encoding in each domain of size n×n×n pixels is carried out OST time, detect the presence of motion in each segment of size n×n pixels by the presence of non-zero spectral coefficients, except the first fragment of the domain in case of presence of motion in each segment of a domain, to eliminate spatial redundancy compute the DCT coefficients (MPC) on two spatial coordinates x and y, the resulting coefficients quantuum, the set of quantized coefficients encode to eliminate spatial redundancy encoded coefficients are passed to the communication channel. In the absence of movement calculate the MPC on the spatial coordinates x and y only for the first fragment, domain, and perform the quantization, encoding and transmission coefficients for �the anal connection. At subsequent stages of coding when receiving packets if the traffic is there, the coding process is repeated if specific domains there is no movement, they transmit a signal about how to use when decoding of the previous fragment. At the reception of the compressed video stream is subjected to decoding, and then dekvantovanie. In the case of motion in domains dekvantovanie coefficients are subjected to inverse DCT-3 (OGK-3) (consistent implementation of the two-dimensional inverse DCT (ADCP-2D) and one-dimensional inverse DCT (ADCP-1D) and as a result restores the original video stream. In the absence of movement in specific domains, transferred in the previous domains, the spectral coefficients are stored in the buffer fragments without motion) recover fragments of these domains when only the inverse discrete cosine transform (ADCP) time and as a result restores the original stream.

The disadvantage of the prototype is that when encoding according to the degree of mobility of the source images by classifying them into two groups: with the lack of movement and the presence of motion. This makes the code less efficient from the standpoint of the achieved compression for a given error recovery at the reception due to insufficient adaptation to the mobility of Cody�creating fragments of the source image.

The aim of the invention is to provide a method of encoding and decoding video data based on the DCT-3, resulting in an increased compression ratio of video data at a predetermined error recovery images at the reception by adapting to changes in the statistical properties of the input images. The adaptation to changes in the statistical properties of the input images is performed by swapping the order of the fragments of the MPC, obtained after performing the DCT-2 along the time axis, then perform DCT-1 so that the total number of nonzero transform coefficients after performing DCT-3 becomes smaller compared to the number of nonzero transform coefficients obtained by performing DCT-3 without performing reordering of fragments DCT-2.

In the claimed method of encoding and decoding video data based on the DCT-3 this object is achieved in that in the known method of encoding and decoding video data based on the DCT-3, namely that compress a sequence of television frames, for which the sequence is divided into packets of n frames, which form the domains of size n×n×n pixels, each domain of size n×n×n pixels perform DCT-3 for removing temporal and spatial redundancy obtained By�KP quantuum, code for eliminating statistical redundancy and transmit to the communication channel, receive from the communication channel, the compressed video stream, the compressed video stream is subjected to decoding, dekvantovanie, OGK-3, as a result, the compressed signal recovery to the original video stream. In this case, after the formation of a domain of size n×n×n pixels is calculated MPC spatial x and y coordinates for each fragment of the domain. Then perform a permutation of the fragments obtained MPC on the spatial coordinates x and y. Remember a permutation as a vector of permutations. After that perform the DCT operation time, the MPC quantuum and code. Next, the resulting quantized MPC and the permutation vector and passed to the communication channel, receive from the communication channel, decode the MPC and the permutation vector, decanted MPC. Over decontaminati MPC perform the operation ADCP time. Reverse permutation of the fragments of the MPC on the spatial coordinates x and y. Restore a domain of size n×n×n pixels by calculating coefficients ADCP on the spatial coordinates x and y, and as a result restores the original stream.

For permutations of fragments obtained MPC on the spatial coordinates x and y previously received over the MPC on the spatial coordinates x and y perform the surgery prep time. �alley quantuum received hcdcp, determine the number NZ of non-zero quantized MPC and remember it. Then, each slice computed by the MPC on the spatial coordinates x and y alternately on the location of the remaining fragments computed by the MPC on the x and y coordinates, and the place of the displaced fragment is computed MPC by coordinates x and y have the fragment computed MPC by coordinates x and y, which is arranged displaced fragment computed MPC by coordinates x and y. Then for obtained after moving the MPC performs a DCT operation on time, quantum and determine the number NZt non-zero quantized MPC. If NZt will be less than previously memorized NZ, we perform the reassignment NZ=NZt and remember the order of the fragments calculated MPC on the spatial coordinates x and y as a vector of permutations. Otherwise restore the previous location of the fragments calculated MPC on the spatial coordinates x and y.

To remember the order of the fragments of the MPC on the spatial coordinates x and y form a permutation vector of size 1×n elements by assigning each element of the Piwhere i=1, 2,..., n number location of corresponding fragment computed by the MPC on the spatial coordinates x and y.

Thanks to the new sosaku�activity of the essential features in the claimed method achieved the specified technical result due to the order along the time axis slices computed by the MPC by coordinates x and y, the total number of non-zero quantized MPC after performing three-dimensional transformation was minimal.

The inventive method is illustrated by drawings on which is shown:

Fig.1 - structural diagram of the inventive method of encoding and decoding video data based on the DCT-3;

Fig.2 - the essence of the claimed method based on DCT-3;

Fig.3 - the formation of the source domain as a three-dimensional array of size n×n×n pixels;

Fig.4 - calculating the MPC on the spatial coordinates x and y;

Fig.5 for an example of the matrix DCT-2 of size 8×8 elements;

Fig.6 - example of DCT-1 calculated over the MPC on the spatial coordinates x and y without permutation and a permutation of the fragments;

Fig.7 is an example of a quantized MPC, after performing one-dimensional DCT without swapping the fragments computed by the MPC on the spatial coordinates x and y along the time axis;

Fig.8 - example of a quantized MPC, after DCT-1 a permutation of the fragments calculated MPC on the spatial coordinates x and y along the time axis;

Fig.9 - example of dependency of the number of nonzero quantized MPC from the number of the fragment.

The possibility of implementing the claimed method of encoding and decoding video data based on the DCT-3 is explained as follows.

Shots of moving images are characterized as �nutriitonal or spatial redundancy, and interframe or temporal redundancy. Typically, in known compression standards N. 263, N.264 to resolve intra-frame redundancy use any decorrelate conversion, for example, DCT-2. To eliminate temporal redundancy using inter-frame prediction on the basis of transmission of motion vectors. In the ways of coding based on the DCT-3 addressing intraframe and interframe redundancy by decorrelation of the pixels of the original image by spatial coordinates x and y, and along the time axis. As a result of decorrelation most of the coefficients DCT-3 is zero or close to zero, which ensures the reduction of the required number of bits needed to encode the coefficients DCT-3. However, according to practical research, decorrelates transformation on the basis of cosine functions is optimal only for a given class of images. This class of images is limited to low frequency (with a small number of small parts) images and, in the case of motion video, images with slow changing scenes in the transition from frame to frame. In practice, the optimality used conversions, especially in the time domain manifests itself in the preservation of a large number of non-zero quantized coefficient�in conversion, that, in turn, reduces the achievable compression ratio. To remedy this deficiency is possible on the basis of implementation of the adaptation procedure in the encoding process in two ways. The first is to change used decorrelates transformation which would take into account the dynamics of change in interframe differences. The second is to change the properties of the input data on which is fixed decorrelate conversion. While transformation of the input data carry out so, to bring them to a form optimal for used decorrelates conversion.

The first option is problematic. This is due not only to the necessity of solving the difficult problem of computing the optimal transformation, but also the need to transfer large amounts of data describing the obtained conversion decoding device via a communication channel with limited bandwidth. Therefore, the inventive method proposes an approach based on changes of the properties of the input data while preserving unchanged used DCT as decorrelates. Modify the properties of the input data is proposed based on the change in the order of the fragments of the coefficients computed from the DCT-2 along the time axis.

Clearly the main idea of proposed method is shown in f�2. In the top left corner shows an example of a domain of size 8×8×8 pixels. Thus the 1st, 2nd, 4th and 8th domain fragments consist of the same pixel is equal to 255 (shown in white), and the 3rd, 5th, 6th and 7th fragments of the domain consist of the same pixels equal to 127 (shown in gray). After performing DCT-2 on each domain fragment obtained 8 fragments of the MPC on the x and y coordinates (upper right corner of Fig.2). All the computed MPC on x and y coordinates of each fragment is equal to zero except for the coefficients with coordinates x=1 and y=1, is equal to 2040, 2040, 1016, 2040, 1016, 1016, 1016 2040 for 1, 2, 3, 4, 5, 6, 7 and 8 fragments, respectively. After performing the DCT-1 calculated on the MPC by coordinates x and y without rearranging fragments received 8 non-zero quantized MPC: 4321, 525, 669, -384, 724, -76, -277, -786. On the other hand, if a permutation of the fragments calculated MPC by coordinates x and y, swapping the 2nd and 5th fragments, there will be obtained 2 non-zero quantized MPC: 4322, 0, 0, 0, 1448, 0, 0, 0. Thus, the permutation of the fragments calculated MPC by coordinates x and y leads to a decrease in the number of non-zero MPC in this example is 4 times that, in turn, leads to higher compression ratio approximately the same time.

A realization of this idea is illustrated by the scheme shown in Fig.1. The input to the encoder receives the domains in the wee�e three-dimensional array of pixels of size n×n×n. The formation of domains of size n×n×n pixels from the package, consisting of n frames of the moving image shown in Fig.3. Then over each of the n fragments of the domain to calculate the MPC for the x and y coordinates, i.e., perform an operation, DCT-2, as shown in Fig.4. This operation is performed in block 11 (DCT-2D of Fig.1). The performance of DCT-2 is carried out, for example, as described in the book: Ahmed N., RAO K. Orthogonal transformation in digital signal processing / edited by I. B. Fomenko; TRANS. angl. - M.: Communication, 1980. Matrix recording of the OST-2 i-th fragment of the source domain is represented by a matrix [A]ithat is:

where [S]i- computed MPC spatial x and y coordinates of the i-th fragment; [G] and [G]T- direct and transpose (inverse) of the matrix DCT-2, defined by an array of vectors{1n,2ncos(2m1)(k1)π2n},m=1, 2,..., n; k=2,3,...,n. Fig.5 shows an example of the matrix DCT-2 of size 8×8 elements.

Next, the slices computed by the MPC by coordinates x and y are fed to a block permutation Permutation of the fragments is carried out so that to the number of nonzero MPC, obtained after performing the DCT-1 along the time axis, is minimal. This operation is performed in block 12 (the permutation of Fig.1). Permutation of the fragments is performed on the basis of the permutation vector, which is computed in the side 16 (the control Block permutation Fig.1) depending on the parameters NZ NZt and derived from the output of the quantization unit. After that perform the DCT operation time in block 13 (DCT-1D of Fig.1). The obtained MPC quantuum in block 14 (quantization Fig.1) and code in block 15 (encoding Fig.1). Next, the resulting quantized MPC and the permutation vector and passed to the communication channel (block the communication channel of Fig.1) take the link. Decode the MPC and the permutation vector. This operation is performed in block 21 (decoding Fig.1). Then decanted MPC in unit 22 (dekvantovanie Fig.1). Over decontaminati MPC perform the operation ADCP time in block 23 (ADCP-1D of Fig.1). Then perform the inverse permutation of the fragments of the MPC on the spatial coordinates x and y in block 24 (the permutation of Fig.1). Then restore a domain of size n×n×n pixels by calculating coefficients ADCP on the spatial coordinates x and y in block 25 (ADCP-2D of Fig.1) and as a result restores the original stream.

For clarity, in Fig.6 the left panel shows the result of performing DCT-1 above calculated� MPC on the spatial coordinates x and y without changes i.e. 1 fragment MPC is located in the first place, the second on the second, etc. the permutation Vector in this case has the form P=[1 2 3 4 5 6 7 8]. The number of nonzero quantized MPC in this example amounted to 107. In the right part of Fig.6 shows the result of the DCT-1 calculated over the MPC on the spatial coordinates x and y after their permutations. Found vector permutations in this example has the form P=[7 5 4 3 1 6 2 8], ie 7 fragment MPC is in first place, 5 for second, etc. in accordance with the permutation vector. The number of nonzero quantized MPC in this case was 88, which is less than in the first case. Examples of quantized MPC, after performing the DCT-1 without rearranging fragments computed by the MPC on the spatial coordinates x and y along the time axis and Perestroikas shown in Fig.7 and 8, respectively.

To evaluate the effectiveness of the proposed method of encoding and decoding based on DCT-3 conducted simulation on the PC. As an indicator of the efficiency coefficient was used reducing the number of non-zero quantized MPC when relocating fragments computed by the MPC on the spatial coordinates x and y on the number of nonzero quantized MPC, obtained without moving.

As the source moving images was used a set of test images�s of size 576×720 pixels in YUV 4:4:4 and frame rate 25 frames/s. The size of the original domain was 8×8×16 pixels.

Fig.9 shows the characteristic dependence of the number of nonzero quantized MPC from fragment:

(a) without rearranging fragments;

b) a permutation of the fragments;

(C) the difference between the number of MPCS obtained by permutation without rearranging.

We define the efficiency ratio asKef=(NbpNpNbp)100%a,

NBP- total number of non-zero quantized MPC, obtained without rearranging fragments; Np- total number of non-zero quantized MPC, obtained by permutation of the fragments.

The simulation results of the developed method showed that the gain was 15÷20% in comparison with the prototype. Studies have shown that reducing the number of non-zero quantized MPC 15÷20% leads to the same value of increasing the compression ratio while maintaining the same quality of the restored images, which confirms the achievement of the objectives of the invention.

1. Method of encoding and decoding VI�geoinformatie based on three-dimensional discrete cosine transform (DCT), namely that compress a sequence of television frames, for which the sequence is divided into packets of n frames, which form the domains of size n×n×n pixels, each domain of size n×n×n pixels perform three-dimensional DCT for removing temporal and spatial redundancy, the resulting DCT coefficients quantuum, code to eliminate the statistical redundancy and transmit to the communication channel, receive from the communication channel, the compressed video stream, the compressed video stream is subjected to decoding, dekvantovanie, three-dimensional inverse DCT, as a result, the compressed signal recovery to the original video stream, wherein after the formation of a domain of size n×n×n pixels compute the DCT coefficients for spatial x and y coordinates for each fragment of the domain, then perform a permutation of the fragments of the received DCT coefficients on the spatial coordinates x and y, remembering a permutation as a vector of permutations, perform a DCT operation on the time, the DCT coefficients quantuum, encode the received quantized DCT coefficients and the vector of permutations and transmit to the communication channel, receive from the communication channel, decode the DCT coefficients and the vector of permutations, decanted DCT coefficients, over decontaminati DCT coefficients perform an operation reverse �KP time reverse permutation of the fragments of the DCT coefficients on the spatial coordinates x and y, restore a domain of size n×n×n pixels by calculating the coefficients of the inverse DCT on the spatial coordinates x and y, and as a result restores the original stream.

2. A method according to claim 1, characterized in that the rearrangement of the fragments of the received DCT coefficients on the spatial coordinates x and y on pre-obtained DCT coefficients on the spatial coordinates x and y perform the operation of prep time, quantuum the received DCT coefficients, determine the number NZ of non-zero quantized DCT coefficients and remember it, then each fragment of the calculated DCT coefficients on the spatial coordinates x and y alternately on the location of the remaining fragments of the calculated DCT coefficients by coordinates x and y, and in place of the displaced fragment of the calculated DCT coefficients in the x and y comprise a fragment of the calculated DCT coefficients in the x and y coordinates, which is arranged displaced fragment of the calculated DCT coefficients by coordinates x and y, obtained after moving the DCT coefficients perform the operation of prep time, quantum and determine the number NZt non-zero quantized coefficients DK� and, if NZt will be less than previously memorized NZ, we perform the reassignment NZ=NZt and remember the order of the fragments of the calculated DCT coefficients on the spatial coordinates x and y as a vector of permutations, otherwise restore the previous location of the fragments of the calculated DCT coefficients on the spatial coordinates x and y.

3. A method according to claim 1, characterized in that for memorizing the order of the fragments of the calculated DCT coefficients on the spatial coordinates x and y form a permutation vector of size 1×n elements by assigning each element of the Piwhere i=1, 2,..., n number location of the corresponding fragment of the calculated DCT coefficients on the spatial coordinates x and y.



 

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22 cl, 2 dwg

FIELD: physics, photography.

SUBSTANCE: invention relates to an image processing device and method, which can improve encoding efficiency, thereby preventing increase in load. The technical result is achieved due to that a selection scheme 71 from a prediction scheme 64 by filtering selects a motion compensation image for generating a prediction image at a high-resolution extension level from key frames at a low-resolution base level. The filter scheme 72 of the prediction scheme 64 by filtering performs filtration, which includes high-frequency conversion and which uses analysis in the time direction of a plurality of motion compensation images at the base level, selected by the selection scheme 71, in order to generate a prediction image at the extension level.

EFFECT: reducing load in terms of the amount of processing owing to spatial increase in sampling frequency at the base level for encoding the current frame.

19 cl, 26 dwg

FIELD: information technology.

SUBSTANCE: method of compression of graphic file by fractal method using ring classification of segments, in which the graphic file is split into rank regions and domains, and for each rank region the domain and the corresponding affine transformation is found, that best approximates it to the appropriate rank region, and using the obtained values of the domain parameters, comprising their coordinates, the coefficients of the affine transformations, the values of brightness and contrast, the archive is formed, and classification of domains and rank regions are introduced, based on the allocation in them of the "rings" and the calculation of the mathematical expectation of pixel intensity of these "rings", which enables to reduce the complexity of the phase of correlation of the segments and to accelerate compression.

EFFECT: reduced time of compression of the graphic file by fractal method.

3 dwg

FIELD: physics.

SUBSTANCE: method comprises making each array element in an image sensor from one "R, G, B radiation colour brightness to code" converter, which performs parallel synchronous conversion of radiation of three colours analogue video signals R, G, B into three codes. The frame image digitisation apparatus includes an objective lens, an image sensor comprising an array of elements, three switch units, three register units and a control signal generator, wherein each switch unit includes the same number of encoders as converters.

EFFECT: reduced cross dimensions of array elements in an image sensor, which enables to reduce the frame format size or increase resolution of the image sensor.

6 dwg, 1 tbl

FIELD: physics.

SUBSTANCE: disclosed is a frame image digitisation apparatus. The disclosed apparatus comprises a lens in the focal plane of which there is an image sensor having an array of elements, a control signal generator and three register units, the outputs of which are the outputs of the digitisation apparatus. Each array element consists of a converter for converting radiation of colours R, G, B into three codes. Images are input into the sensor, the number of said images being equal to the number of array elements and the number of colours R, G, B of analogue-to-digital converters (ADC).

EFFECT: high image frame resolution owing to conversion of three colours R, G, B into codes using one converter.

4 dwg, 2 tbl

FIELD: systems for encoding and decoding video signals.

SUBSTANCE: method and system for statistical encoding are claimed, where parameters which represent the encoded signal are transformed to indexes of code words, so that decoder may restore the encoded signal from aforementioned indexes of code words. When the parameter space is limited in such a way that encoding becomes inefficient and code words are not positioned in ordered or continuous fashion in accordance with parameters, sorting is used to sort parameters into various groups with the goal of transformation of parameters from various groups into indexes of code words in different manner, so that assignment of code word indexes which correspond to parameters is performed in continuous and ordered fashion. Sorting may be based on absolute values of parameters relatively to selected value. In process of decoding, indexes of code words are also sorted into various groups on basis of code word index values relatively to selected value.

EFFECT: increased efficiency of compression, when encoding parameters are within limited range to ensure ordered transformation of code word indexes.

6 cl, 3 dwg

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