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Video coding and processing: A survey

NEUROCOMPUTING 2020年 408卷 331-344页

作者： Liu, Yunxia Liu, Si Wang, Yonghao Zhao, Hongguo Zhengzhou Normal Univ Coll Informat Sci & Technol Zhengzhou Peoples R China Birmingham City Univ Comp & Digital Technol Birmingham W Midlands England

Vision is the main way for people to perceive and recognize the world. In this paper, four categories of the redundant information of video encoding, spatial redundancy, time redundancy, visual redundancy and statistical redundancy, are first introduced. Spatial redundancy is redundant information existing in static frames, time redundancy is the luminance and chrominance correlation between adjacent frames in the video sequence, visual redundancy is information that the human visual system cannot perceive, statistical redundancy is the expression redundancy of the information source symbols. Then the performance assessment of video coding are introduced. And the future development of video coding and conclusion are finally discussed in this paper. (c) 2020 Elsevier B.V. All rights reserved.

关键词： Video coding Redundant information Intra prediction Inter prediction Transform entropy coding

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On the structure of optimal entropy-constrained scalar quantizers

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IEEE TRANSACTIONS ON INFORMATION THEORY 2002年第2期48卷 416-427页

作者： György, A Linder, T Budapest Univ Technol & Econ Dept Comp Sci & Informat Theory H-1521 Budapest Hungary Queens Univ Dept Math & Stat Kingston ON K7L 3N6 Canada

The nearest neighbor condition implies that when searching for a mean-square optimal fixed-rate quantizer it is enough to consider the class of regular quantizers, i.e., quantizers having convex cells and codepoints which lie inside the associated cells. In contrast, quantizer regularity can preclude optimality in entropy-constrained quantization. This can be seen by exhibiting a simple discrete scalar source for which the mean-square optimal entropy-constrained scalar quantizer (ECSQ) has disconnected (and hence nonconvex) cells at certain rates. In this work, new results concerning the structure and existence of optimal ECSQs are presented. One main result shows that for continuous sources and distortion measures of the form d(x, y) = rho(\x - y\), where rho is a nondecreasing convex function, any finite-level ECSQ can be "regularized" so that the resulting regular quantizer has the same entropy and equal or less distortion. Regarding the existence of optimal ECSQs, we prove that under rather general conditions there exists an "almost regular" optimal ECSQ for any entropy constraint. For the squared error distortion measure and sources with piecewise-monotone and continuous densities, the existence of a regular optimal ECSQ is shown.

关键词： convex distortion measures entropy coding optimal quantization regular quantizers

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Multirate Progressive entropy Model for Learned Image Compression

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2024年第8期34卷 7725-7741页

作者： Li, Chao Yin, Shanzhi Jia, Chuanmin Meng, Fanyang Tian, Yonghong Liang, Yongsheng Harbin Inst Technol Sch Elect & Informat Engn Shenzhen 518055 Guangdong Peoples R China City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China Peking Univ Natl Engn Res Ctr Visual Technol Sch Comp Sci Beijing 100871 Peoples R China Peng Cheng Lab Shenzhen 518055 Peoples R China

This paper proposes a unified and efficient entropy coding method for learned image compression (LIC) from the perspective of traditional signal processing. First, the consistency of structures and optimization objectives are used to interpret the existing split-coded-then-merge entropy coding strategies in LIC as a particular filter banks framework, with feature separation and feature aggregation representing the analysis filter bank and synthesis filter bank, respectively. Thus, we borrow the design from the multirate filter banks and proposed Multirate Progressive entropy Model (MPEM) to enhance the rate-distortion performance and decoding speed. In particular, we create an analysis filter bank that divides compact features into a few nonuniform subsets based on various spatial and channel sampling rates. Then multi-scale detail and mean coefficients within the current subset are used as prior representations to help generate the prediction parameters of the next subset, and the carefully designed synthetic filter bank performs a near-perfect reconstruction of the features. In addition, we propose a Multi-level Edge Attention Moudal (MEAM) to increase the edge and texture information's contribution and reduce the high-frequency information loss brought on by MPEM's inherent multi-rate spatial sampling, which leverages the edge operator and structural reparameterization principles. The results of the experiments show that, in comparison to the effective LIC methods and traditional code, the proposed MPEM can decode data at a cutting-edge speed while also offering comparable rate-distortion performance.

关键词： entropy Filter banks Context modeling Image coding Decoding entropy coding Computational modeling Deep learning image compression multi-rate filter bank entropy model attention mechanism

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Transform coding with integer-to-integer transforms

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IEEE TRANSACTIONS ON INFORMATION THEORY 2000年第2期46卷 465-473页

作者： Goyal, VK Lucent Technol Bell Labs Math Commun Res Dept Murray Hill NJ 07974 USA

A new interpretation of transform coding is developed that downplays quantization and emphasizes entropy coding, allowing a comparison of entropy coding methods with different memory requirements. With conventional transform coding, based on computing Karhunen-Loeve transform coefficients acid then quantizing them, vector entropy coding can be replaced by scalar entropy coding without an increase in rate, Thus the transform coding advantage is a reduction in memory requirements for entropy coding. This paper develops a transform coding technique where the source samples are first scalar-quantized and then transformed with an integer-to-integer approximation to a nonorthogonal linear transform. Among the possible advantages is to reduce the memory requirement further than conventional transform coding by using a single common scalar entropy codebook for all components. The analysis shows that for high-rate coding of a Gaussian source, this reduction in memory requirements comes without any degradation of rate-distortion performance.

关键词： entropy coding Gaussian sources memory reduction transform coding

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Multiple-Description coding by Dithered Delta-Sigma Quantization

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IEEE TRANSACTIONS ON INFORMATION THEORY 2009年第10期55卷 4661-4675页

作者： Ostergaard, Jan Zamir, Ram Aalborg Univ Dept Elect Syst Aalborg Denmark Tel Aviv Univ Dept Elect Engn Syst IL-69978 Tel Aviv Israel

We address the connection between the multiple-description (MD) problem and Delta-Sigma quantization. The inherent redundancy due to oversampling in Delta-Sigma quantization, and the simple linear-additive noise model resulting from dithered lattice quantization, allow us to construct a symmetric and time-invariant MD coding scheme. We show that the use of a noise-shaping filter makes it possible to trade off central distortion for side distortion. Asymptotically, as the dimension of the lattice vector quantizer and order of the noise-shaping filter approach infinity, the entropy rate of the dithered Delta-Sigma quantization scheme approaches the symmetric two-channel MD rate-distortion function for a memoryless Gaussian source and mean square error (MSE) fidelity criterion, at any side-to-central distortion ratio and any resolution. In the optimal scheme, the infinite-order noise-shaping filter must be minimum phase and have a piecewise flat power spectrum with a single jump discontinuity. An important advantage of the proposed design is that it is symmetric in rate and distortion by construction, so the coding rates of the descriptions are identical and there is therefore no need for source splitting.

关键词： Delta-Sigma modulation dithered lattice quantization entropy coding joint source-channel coding multiple-description (MD) coding vector quantization

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Optimising lossless stages in a GPU-based MPEG encoder

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MULTIMEDIA TOOLS AND APPLICATIONS 2013年第3期65卷 495-520页

作者： Montero, Pablo Gulias, Victor M. Taibo, Javier Rivas, Samuel CITIC MADS Grp La Coruna 15008 Spain

Modern GPUs excel in parallel computations, so they are an interesting target to perform matrix transformations such as the DCT, a fundamental part of MPEG video coding algorithms. Considering a system to encode synthetic video (e.g., computer-generated frames), this approach becomes even more appealing, since the images to encode are already in the GPU, eliminating the costs of transferring raw video from the CPU to the GPU. However, after a raw frame has been transformed and quantized by the GPU, the resulting coefficients must be reordered, entropy encoded and framed into the resulting MPEG bitstream. These last steps are essentially sequential and their straightforward GPU implementation is inefficient compared to CPU-based implementations. We present different approaches to implement part of these steps in GPU, aiming for a better usage of the memory bus, compensating the suboptimal use of the GPU with the gains in transfer time. We analyze three approaches to perform the zigzag scan and Huffman coding combining GPU and CPU, and two approaches to assemble the results to build the actual output bitstream both in GPU and CPU memory. Our experiments show that optimising the amount of data transferred from GPU to CPU implementing the last sequential compression steps in the GPU, and using a parallel fast scan implementation of the zigzag scanning improve the overall performance of the system. Savings in transfer time outweigh the extra cost incurred in the GPU.

关键词： Zigzag scan Huffman coding GPU Video compression MPEG entropy coding

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A Highly Parallel and Scalable CABAC Decoder for Next Generation Video coding

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IEEE JOURNAL OF SOLID-STATE CIRCUITS 2012年第1期47卷 8-22页

作者： Sze, Vivienne Chandrakasan, Anantha P. Texas Instruments Inc Syst & Applicat R&D Ctr Dallas TX 75432 USA MIT Microsyst Technol Labs Cambridge MA 02139 USA

Future video decoders will need to support high resolutions such as Quad Full HD (QFHD, 4096 x 2160) and fast frame rates (e. g., 120 fps). Many of these decoders will also reside in portable devices. Parallel processing can be used to increase the throughput for higher performance (i.e., processing speed), which can be traded-off for lower power with voltage scaling. The next generation standard called High Efficiency Video coding (HEVC), which is being developed as a successor to H.264/AVC, not only seeks to improve the coding efficiency but also to account for implementation complexity and leverage parallelism to meet future power and performance demands. This paper presents a silicon prototype for a pre-standard algorithm developed for HEVC ("H.265") called Massively Parallel CABAC (MP-CABAC) that addresses a key video decoder bottleneck. A scalable test chip is implemented in 65-nm and achieves a throughput of 24.11 bins/cycle, which enables it to decode the max H.264/AVC bit-rate (300 Mb/s) with only a 18 MHz clock at 0.7 V, while consuming 12.3 pJ/bin. At 1.0 V, it decodes a peak of 3026 Mbins/s for a bit-rate of 2.3 Gb/s, enough for QFHD at 186 fps. Both architecture and joint algorithm-architecture optimizations used to reduce critical path delay, area cost and memory size are discussed.

关键词： CABAC CMOS digital integrated circuits entropy coding HEVC H.264/AVC low-power electronics parallel algorithms parallel architectures video codecs video coding

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The JPEG 2000 still image compression standard

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IEEE SIGNAL PROCESSING MAGAZINE 2001年第5期18卷 36-58页

作者： Skodras, A Christopoulos, C Ebrahimi, T Univ Patras Elect Lab GR-26110 Patras Greece Comp Technol Inst GR-26110 Patras Greece Ericsson Res Ericssons Medilab Stockholm Sweden

One of the aims of the standardization committee has been thedevelopment of Part I, which could be used on a royalty- and fee-freebasis. This is important for the standard to become widely accepted. Thestandardization process, which is coordinated by the JTCI/SC29/WG1 ofthe ISO/IEC has already produced the international standard (IS) forPart I. In this article the structure of Part I of the JPFG 2000standard is presented and performance comparisons with establishedstandards are reported. This article is intended to serve as a tutorialfor the JPEG 2000 standard. The main application areas and theirrequirements are given. The architecture of the standard follows withthe description of the tiling, multicomponent transformations, wavelettransforms, quantization and entropy coding. Some of the mostsignificant features of the standard are presented, such asregion-of-interest coding, scalability, visual weighting, errorresilience and file format aspects. Finally, some comparative resultsare reported and the future parts of the standard are discussed

关键词： ISO standards code standards data compression entropy codes image coding quantisation (signal) reviews standardisation telecommunication standards transform coding wavelet transforms ISO/IEC JPEG 2000 still image compression standard Part I standard entr code standards ISO standard image coding Data compression entropy coding transform coding Standardization wavelet transforms

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An Efficient DCT-Based Image Compression System Based on Laplacian Transparent Composite Model

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2015年第3期24卷 886-900页

作者： Sun, Chang Yang, En-Hui Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

Recently, a new probability model dubbed the Laplacian transparent composite model (LPTCM) was developed for DCT coefficients, which could identify outlier coefficients in addition to providing superior modeling accuracy. In this paper, we aim at exploring its applications to image compression. To this end, we propose an efficient nonpredictive image compression system, where quantization (including both hard-decision quantization (HDQ) and soft-decision quantization (SDQ)) and entropy coding are completely redesigned based on the LPTCM. When tested over standard test images, the proposed system achieves overall coding results that are among the best and similar to those of H.264 or HEVC intra (predictive) coding, in terms of rate versus visual quality. On the other hand, in terms of rate versus objective quality, it significantly outperforms baseline JPEG by more than 4.3 dB in PSNR on average, with a moderate increase on complexity, and ECEB, the state-of-the-art nonpredictive image coding, by 0.75 dB when SDQ is OFF (i.e., HDQ case), with the same level of computational complexity, and by 1 dB when SDQ is ON, at the cost of slight increase in complexity. In comparison with H.264 intracoding, our system provides an overall 0.4-dB gain or so, with dramatically reduced computational complexity;in comparison with HEVC intracoding, it offers comparable coding performance in the high-rate region or for complicated images, but with only less than 5% of the HEVC intracoding complexity. In addition, our proposed system also offers multiresolution capability, which, together with its comparatively high coding efficiency and low complexity, makes it a good alternative for real-time image processing applications.

关键词： Image coding transparent composite model (TCM) outlier quantization entropy coding

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Biased Run-Length coding of Bilevel Classification Label Maps of Hyperspectral Images

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2017年第10期10卷 4580-4588页

作者： Liaghati, Amir Leon Pan, W. David Jiang, Zhuocheng Boeing Co Huntsville AL 35824 USA Univ Alabama Dept Elect & Comp Engn Huntsville AL 35899 USA

For efficient coding of bilevel sources with some dominant symbols often found in classification label maps of hyperspectral images, we proposed a novel biased run-length (BRL) coding method, which codes the most probable symbols separately from other symbols. To determine the conditions in which the BRL coding method would be effective, we conducted an analysis of the method using statistical models. We first analyzed the effect of 2-D blocking of pixels, which were assumed to have generalized Gaussian distributions. The analysis showed that the resulting symbol blocks tended to have lower entropies than the original source without symbol blocking. We then analyzed the BRL coding method applied on the sequence of block symbols characterized by a first-order Markov model. Information-theoretic analysis showed that the BRL coding method tended to generate codewords that have lower entropies than the conventional run-length coding method. Furthermore, numerical simulations on lossless compression of actual data showed improvement of the state of the art. Specifically, end-to-end implementation integrating symbol blocking, BRL, and Huffman coding achieved up to 4.3% higher compression than the JBIG2 standard method and up to 3.2% higher compression than the conventional run-length coding method on classification label maps of the widely used "Indian Pines" dataset.

关键词： Data compression entropy coding hyperspectral imaging image classification

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