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Fast entropy Decoding Method for High Resolution Personal Video Recorder

IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 2009年第3期55卷 1364-1372页

作者： Lee, Sunyoung Lee, Myungjung Yie, Alex Chungku Jang, Euee S. Hanyang Univ Digital Media Lab Dept Elect Comp Engn Seoul 133791 South Korea Hanyang Univ Digital Media Lab Dept Comp Engn Seoul 133791 South Korea

In this paper, we propose a fast entropy decoding method that is well suited for personal video recorder (PVR) applications for high resolution video (HRV). In PVR applications supporting HRV, it is essential to implement a fast encoder and decoder due to the large amount of video data. The proposed bit-precision based entropy method (BPEM) provides a way to design a very simple entropy decoding process, which can substantially reduce the overall computational complexity of the decoder. For the purpose of contents protection, it is common to have a proprietary codec in PVR. In such a case, additional transcoding for storing transmitted data is required. However, this may involve a complex process that requires encoding and decoding. The proposed method is only applied to the entropy coding method of the existing standard codecs for transcoding thereby reducing the transcoding complexity down to bitstream-level symbol mapping. We implemented BPEM on an MPEG-4 simple profile (SP) codec. The experimental results showed that BPEM produced about 30 percent lower decoder complexity and 50 to 80 percent lower syntax parsing time while maintaining similar coding efficiency, compared to the conventional MPEG-4 SP codec.

关键词： Personal video recorder High resolution video entropy coding Video compression

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Double bit range estimation with eight estimators for CABAC in VVC

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IET IMAGE PROCESSING 2022年第12期16卷 3155-3163页

作者： Chan, Ka-Hou Im, Sio-Kei Macao Polytech Univ Fac Appl Sci Taipa Macau Peoples R China Macao Polytech Univ Taipa Macau Peoples R China

This work describes the modification of Context-based Adaptive Binary Arithmetic coding (CABAC) using the double bit range estimation in the VVC engine and the consideration of range updates by using eight hypothetical probability estimators. The focus is on the selected adaptation rates performed in these proposed estimators, which are chosen based on memory consideration and coding efficiency. An investigation of arithmetic coding engines with multi-hypothesis probability estimates and their consideration of contextual modeling of entropy coding at the level of transform coefficients. The proposed scheme enables a quantitative representation of probabilistic predictions linearly and describes the scalability potential for higher accuracy. In addition, this work discusses the hardware implementation, which is based on simple operations such as bitwise operations and subinterval updates. The experimental results validate the effectiveness of the proposed approach specified in VTM framework. The improved results show that it provides more significant gains in terms of RA and LD, which is better than the AI configuration.

关键词： hypothetical probability estimators memory consideration VVC engine probability arithmetic coding engines Context-based Adaptive Binary Arithmetic coding double bit range estimation multihypothesis probability estimates binary codes entropy coding entropy codes range updates selected adaptation rates coding efficiency CABAC adaptive codes arithmetic codes video coding

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Analysis of the Limitations of Further Improvement of the Efficiency of VVC-CABAC

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IEEE ACCESS 2023年 11卷 16793-16800页

作者： Karwowski, Damian Domanski, Marek Peng, Wen-Hsiao Hang, Hsueh-Ming Poznan Univ Tech Fac Comp & Telecommun PL-60965 Poznan Poland Natl Yang Ming Chiao Tung Univ Inst Data Sci Hsinchu 30010 Taiwan Natl Yang Ming Chiao Tung Univ Inst Elect Hsinchu 30010 Taiwan

Hybrid video compression plays an invaluable role in digital video transmission and storage services and systems. It performs several-hundred-fold reduction in the amount of video data, which makes these systems much more efficient. An important element of hybrid video compression is entropy coding of the data. The state-of-the-art in this field is the newest variant of the Context-based Adaptive Binary Arithmetic coding entropy compression algorithm which recently became part of the new Versatile Video coding technology. This work is a part of research that is currently underway to further improve the Context-based Adaptive Binary Arithmetic coding technique. This paper provides analysis of the potential for further improvement of the Context-based Adaptive Binary Arithmetic coding technique by more accurate calculation of probabilities of data symbols. The mentioned technique calculates those probabilities by the use of idea of the two-parameters hypothesis. For the needs of analysis presented in this paper, an extension of the aforementioned idea was proposed which consists of three- and four-parameters hypothesis. In addition, the paper shows the importance of proper calibration of parameter values of the method on efficiency of data compression. Results of experiments show that for the considered in the paper variants of the algorithm improvement the possible efficiency gain is at levels 0.11% and 0.167%, for the three- and four-parameter hypothesis, respectively.

关键词： Streaming media Estimation Probability Syntactics Symbols entropy coding Arithmetic Video compression Probability estimation entropy coding arithmetic coding VVC-CABAC video compression

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Optimal variable-rate mean-gain-shape vector quantization for image coding

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 1996年第6期6卷 660-668页

作者： Lightstone, M Mitra, SK UNIV CALIF SANTA BARBARA CTR INFORMAT PROC RESDEPT ELECT & COMP ENGNSANTA BARBARACA 93106

A method for rate-distortion optimal variable rate mean-gain-shape vector quantization (MGSVQ) is presented with application to image compression, Conditions are derived within an entropy-constrained product code framework that result in an optimal bit allocation between mean, gain, and shape vectors at all rates, An extension to MGSVQ called hierarchical mean-gain-shape vector quantization (HMGSVQ) is similarly introduced, By considering statistical dependence between adjacent means, this method is able to provide improvement in rate-distortion performance over traditional MGSVQ, especially at low bit rates, Simulation results are provided to demonstrate the rate-distortion performance of MGSVQ and HMGSVQ for image data.

关键词： entropy codes image coding optimisation rate distortion theory statistical analysis vector quantisation HMGSVQ MGSVQ entropy constrained product code gain vectors hierarchical mean gain shape vector quantization image compression image data low bit rates image coding image data Rate distortion Vector quantization Rate distortion theory Data compression Statistical analysis Image compression entropy coding Statistical methods

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Structured prefix codes for quantized low-shape-parameter generalized Gaussian sources

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IEEE TRANSACTIONS ON INFORMATION THEORY 1999年第4期45卷 1307-1314页

作者： Wen, JT Villasenor, JD Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90024 USA

The highly peaked wide-tailed pdf's that are encountered in many image coding algorithms are often modeled using the family of generalized Gaussian (GG) pdf's. We study entropy coding of quantized GG sources using prefix codes that are highly structured, and which therefore involve low computational complexity to utilize. We provide bounds for the redundancy associated with applying these codes. to quantized GG sources. We also explore code efficiency and code choice for a wide range of GG source and quantizer parameters.

关键词： entropy coding memoryless generalized Gaussian sources prefix codes quantization

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Convolutional Neural Network-Based Arithmetic coding for HEVC Intra-Predicted Residues

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2020年第7期30卷 1901-1916页

作者： Ma, Changyue Liu, Dong Peng, Xiulian Li, Li Wu, Feng Univ Sci & Technol China CAS Key Lab Technol Geospatial Informat Proc & Ap Hefei 230027 Peoples R China Microsoft Res Asia Beijing 100080 Peoples R China Univ Missouri Kansas City MO 64111 USA

entropy coding is a fundamental technology in video coding that removes statistical redundancy among syntax elements. In high efficiency video coding (HEVC), context-adaptive binary arithmetic coding (CABAC) is adopted as the primary entropy coding method. The CABAC consists of three steps: binarization, context modeling, and binary arithmetic coding. As the binarization processes and context models are both manually designed in CABAC, the probability of the syntax elements may not be estimated accurately, which restricts the coding efficiency of CABAC. To address the problem, we propose a convolutional neural network-based arithmetic coding (CNNAC) method and apply it to compress the syntax elements of the intra-predicted residues in HEVC. Instead of manually designing the binarization processes and context models, we propose directly estimating the probability distribution of the syntax elements with a convolutional neural network (CNN), as CNNs can adaptively build complex relationships between inputs and outputs by training with a lot of data. Then, the values of the syntax elements, together with their estimated probability distributions, are fed into a multi-level arithmetic codec to perform entropy coding. In this paper, we have utilized the CNNAC to code the syntax elements of the DC coefficient;the lowest frequency AC coefficient;the second, third, fourth, and fifth lowest frequency AC coefficients;and the position of the last non-zero coefficient in the HEVC intra-predicted residues. The experimental results show that our proposed method achieves up to 6.7% BD-rate reduction and an average of 4.7% BD-rate reduction compared to the HEVC anchor under all intra (AI) configuration.

关键词： Syntactics Context modeling Video coding entropy coding Estimation Convolutional neural networks Arithmetic coding context-adaptive binary arithmetic coding (CABAC) convolutional neural network-based arithmetic coding (CNNAC) entropy coding high efficiency video coding (HEVC) intra-predicted residues

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Multicore Parallelism Exploration Targeting 3D-HEVC Intra-Frame Prediction

IEEE DESIGN & TEST

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IEEE DESIGN & TEST 2020年第3期37卷 15-21页

作者： Sanchez, Gustavo Fernandes, Ramon Cataldo, Rodrigo Agostini, Luciano Sousa, Leonel Marcon, Cesar Pontifical Catholic Univ Rio Grande Sul PUCRS Porto Alegre RS Brazil Univ Lisbon Lisbon Portugal If Farroupilha Alegrete Brazil

Editor's note: The usage of multicore architectures for 3D-HEVC intraframe prediction is of great benefit, especially to improve the performance, throughput, and even the energy consumption in systems. Multicore hardware is used in all high-performance image processing applications, and also in mobile devices such as cellphones. The distribution of the algorithm to different parallel processor architecture is discussed and evaluated in this article.--ichael Hubner, Brandenburg University of Technology

关键词： Tools Parallel processing Instruction sets Multicore processing Three-dimensional displays entropy coding Intra-Frame Prediction 3D-HEVC Multicore Parallelism Exploration

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entropy-CONSTRAINED VECTOR QUANTIZATION

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IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING 1989年第1期37卷 31-42页

作者： CHOU, PA LOOKABAUGH, T GRAY, RM COMPRESSION LABS INC SAN JOSE CA 95134 USA STANFORD UNIV DEPT ELECT ENGN INFORMAT SYST LAB STANFORD CA 94305 USA

An iterative descent algorithm based on a Lagrangian formulation for designing vector quantizers having minimum distortion subject to an entropy constraint is discussed. These entropy-constrained vector quantizers (ECVQs) can be used in tandem with variable-rate noiseless coding systems to provide locally optimal variable-rate block source coding with respect to a fidelity criterion. Experiments on sampled speech and on synthetic sources with memory indicate that for waveform coding at low rates (about 1 bit/sample) under the squared error distortion measure, about 1.6 dB improvement in the signal-to-noise ratio can be expected over the best scalar and lattice quantizers when block entropy-coded with block length 4. Even greater gains are made over other forms of entropy-coded vector quantizers. For pattern recognition, it is shown that the ECVQ algorithm is a generalization of the k-means and related algorithms for estimating cluster means, in that the ECVQ algorithm estimates the prior cluster probabilities as well. Experiments on multivariate Gaussian distributions show that for clustering problems involving classes with widely different priors, the ECVQ outperforms the k-means algorithm in both likelihood and probability of error.

关键词： waveform coding algorithms quantizer Gaussian distribution K-means algorithm Distortion measurement entropy coding

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Joint source-channel decoding for H.264 coded video stream

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IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 2005年第4期51卷 1273-1276页

作者： Wang, Y Yu, SY Shanghai Jiao Tong Univ Inst Image Commun & Informat Proc Res Shanghai 200030 Peoples R China

H.264 is the newest video coding standard and has achieved a significant improvement in coding efficiency. The entropy coding methods used in H.264 are CAVLC and CABAL Although these two variable length code methods can achieve high compression, they are very sensitive to channel errors. This paper presents a joint source-channel MAP (maximum a posteriori probability) decoding method to dealing with this sensitivity to channel errors and applied it to the decoding of the motion vector in H.264 coded video stream. Although H.264 codec has proposed several error resilience methods, we believe this method could provide additional error resilience to H.264 stream. Experiment indicates that our JSCD achieves significant improvement than a separate scheme.

关键词： H.264 entropy coding joint source channel decoding (JSCD) error resilience

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VARIABLE-RATE PREDICTIVE RESIDUAL VECTOR QUANTIZER

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IEEE SIGNAL PROCESSING LETTERS 1995年第4期2卷 70-72页

作者： RIZVI, SA NASRABADI, NM Department of Electrical and Computer Engineering State University of New York University at Buffalo Amherst NY USA

A major problem with a VQ-based image compression scheme is its codebook search complexity, Recently, a predictive residual vector quantizer (PRVQ) was proposed in [4], This scheme has a very low search complexity, and its performance is very close to that of the predictive vector quantizer (PVQ), This letter presents a new VQ scheme called variable-rate PRVQ (VR-PRVQ), which is designed by imposing a constraint on the output entropy of the PRVQ, The proposed VR-PRVQ is found to give an excellent rate-distortion performance and deafly outperforms the state-of-the-art image compression algorithm developed by the Joint Photographic Experts Group (JPEG).

关键词： Bit rate Rate-distortion Algorithm design and analysis Transform coding Image coding Quantization Computational complexity Encoding entropy coding Design methodology

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