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Context-Based 2D-VLC entropy coder in AVS Video Coding Standard

Journal of Computer Science & Technology 2006年第3期21卷 315-322页

作者：王强赵德斌高文 Department of Computer Science and Technology Harbin Institute of Technology Harbin 150001 P.R. China Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 P.R. China

In this paper, a Context-based 2D Variable Length Coding （C2DVLC） method for coding the transformed residuals in AVS video coding standard is presented. One feature in C2DVLC is the usage of multiple 2D-VLC tables and another feature is the usage of simple Exponential-Golomb codes. C2DVLC employs context-based adaptive multiple table coding to exploit the statistical correlation between DCT coefficients of one block for higher coding efficiency. ExpGolomb codes are applied to code the pairs of the run-length of zero coefficients and the nonzero coefficient for lower storage requirement. C2DVLC is a low complexity coder in terms of both computational time and memory requirement. The experimental results show that C2DVLC can gain 0.34dB in average for the tested videos when compared with the traditional 2D-VLC coding method like that used in MPEG-2. And compared with CAVLC in H.264/AVC, C2DVLC shows similar coding efficiency.

关键词： entropy coder context-based video coding VLC

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A low-cost Exp_Golomb hardware architecture for H.264/AVC entropy coder 30

A low-cost Exp_Golomb hardware architecture for H.264/AVC en...

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30th International Conference on Microelectronics (ICM)

作者： Asma, Ben Hamida Salah, Dhahri Abdelkrim, Zitouni Univ Monastir Fac Sci Monastir Lab Elect & Microelect LAB IT06 Monastir 5019 Tunisia Univ Dammam Coll Educ Jubail POB 2435 Dammam 31451 Saudi Arabia

ISBN: (纸本)9781538681671

The Exponential Golomb and Context Adaptive Variable Length Coding are the entropy eoding tools for H.264/AVC in baseline proffle. Since the Exp_Golomb is based on variable length codes with a regular construction, strong error resilience is achieved. However, its hardware implementation causes a challenge due to the logarithmic operation. This paper presents a low-cost hardware architecture for Exp_Golomb. Furthermore, a "shift number counting method" is proposed to solve the key problem of logarithmic operation. This method can significantly simplify the hardware architecture and reduce the area cost. The proposed design has been synthesized with ISE Xilinx on Virtex IV and functionally verified by RTL simulations. The results show that the proposed design occupies 126 LUT slice and has a clock frequency about 250 MHz.

关键词： Exp_Golomb entropy coder blurry logarithm H.264

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Further GPU Implementation of Prediction-Based Lower Triangular Transform Using a Zero-Order entropy coder for Ultraspectral Sounder Data Compression

Further GPU Implementation of Prediction-Based Lower Triangu...

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Conference on High-Performance Computing in Remote Sensing II

作者： Wei, Shih-Chieh Huang, Bormin Univ Wisconsin Ctr Space Sci & Engn 1225 W Dayton St Madison WI 53706 USA Tamkang Univ Dept Informat Management Tamsui 25137 Taiwan

ISBN: (纸本)9780819492791

The ultraspectral sounder data consists of two dimensional pixels, each containing thousands of channels. In retrieval of geophysical parameters, the sounder data is sensitive to noises. Therefore lossless compression is highly desired for storing and transmitting the huge volume data. The prediction-based lower triangular transform (PLT) features the same de-correlation and coding gain properties as the Karhunen-Loeve transform (KLT), but with a lower design and implementational cost. In previous work, we have shown that PLT has the perfect reconstruction property which allows its direct use for lossless compression of sounder data. However PLT is time-consuming in doing compression. To speed up the PLT encoding scheme, we have recently exploited the parallel compute power of modern graphics processing unit (GPU) and implemented several important transform stages to compute the transform coefficients on GPU. In this work, we further incorporated a GPU-based zero-order entropy coder for the last stage of compression. The experimental result shows that our full implementation of the PLT encoding scheme on GPU shows a speedup of 88x compared to its original full implementation on CPU.

关键词： prediction-based lower triangular transform graphics processing unit entropy coder

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entropy coders for image compression based on binary forward classification

Entropy coders for image compression based on binary forward...

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Conference on Applications of Digital Image Processing XXIII

作者： Yoo, H Jeong, J Hanyang Univ Dept Elect Commun Engn Seoul 133791 South Korea

ISBN: (纸本)0819437603

entropy coders as a noiseless compression method are widely used as final step compression for images, and there have been many contributions to increase of entropy coder performance and to reduction of entropy coder complexity. In this paper, we propose some entropy coders based on the binary forward classification (BFC). The BFC requires overhead of classification but there is no change between the amount of input information and the total amount of classified output information, which we prove this property in this paper. And using the proved property, we propose entropy coders that are the BFC followed by Golomb-Rice coders (BFC+GR) and the BFC followed by arithmetic coders (BFC+A). The proposed entropy coders introduce negligible additional complexity due to the BFC. Simulation results also show better performance than other entropy coders that have similar complexity to the proposed coders.

关键词： image compression entropy coder Golomb-Rice coder forward classification

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IMAGE STORAGE ON SYNTHETIC DNA USING COMPRESSIVE AUTOENcoderS AND DNA-ADAPTED entropy coderS 25

IMAGE STORAGE ON SYNTHETIC DNA USING COMPRESSIVE AUTOENCODER...

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25th IEEE International Workshop on Multimedia Signal Processing (MMSP)

作者： Pic, Xavier San Antonio, Eva Gil Dimopoulou, Melpomeni Antonini, Marc Cote dAzur Univ I3S Lab 2000 Rte LuciolesEuclide B Sophia Antipolis France CNRS UMR 7271 2000 Rte LuciolesEuclide B Sophia Antipolis France

ISBN: (纸本)9798350338935

Over the past years, the ever-growing trend on data storage demand, more specifically for "cold" data (rarely accessed data), has motivated research for alternative systems of data storage. Because of its biochemical characteristics, synthetic DNA molecules are now considered as serious candidates for this new kind of storage. This paper presents some results on lossy image compression methods based on convolutional autoencoders adapted to DNA data storage, with synthetic DNA-adapted entropic and fixed-length codes. The model architectures presented here have been designed to efficiently compress images, encode them into a quaternary code, and finally store them into synthetic DNA molecules. This work also aims at making the compression models better fit the problematics that we encounter when storing data into DNA, namely the fact that the DNA writing, storing and reading methods are error prone processes. The main take aways of this kind of compressive autoencoder are our latent space quantization and the different DNA adapted entropy coders used to encode the quantized latent space, which are an improvement over the fixed length DNA adapted coders that were previously used.

关键词： image compression DNA autoencoder entropy coder

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Medical Image Compression using Adaptive Subband Threshold

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JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2016年第2期11卷 499-507页

作者： Vidhya, K. Vel Tech Dept Elect & Commun Engn Madras Tamil Nadu India

Medical imaging techniques such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT) and Ultrasound (US) produce a large amount of digital medical images. Hence, compression of digital images becomes essential and is very much desired in medical applications to solve both storage and transmission problems. But at the same time, an efficient image compression scheme that reduces the size of medical images without sacrificing diagnostic information is required. This paper proposes a novel threshold-based medical image compression algorithm to reduce the size of the medical image without degradation in the diagnostic information. This algorithm discusses a novel type of thresholding to maximize Compression Ratio (CR) without sacrificing diagnostic information. The compression algorithm is designed to get image with high optimum compression efficiency and also with high fidelity, especially for Peak Signal to Noise Ratio (PSNR) greater than or equal to 36 dB. This value of PSNR is chosen because it has been suggested by previous researchers that medical images, if have PSNR from 30 dB to 50 dB, will retain diagnostic information. The compression algorithm utilizes one-level wavelet decomposition with threshold-based coefficient selection.

关键词： Discrete wavelet transform Medical imaging Image compression entropy coder Performance measures

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Optimal normalisation of prediction residual for predictive coding with random access

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IET SIGNAL PROCESSING 2014年第7期8卷 710-719页

作者： Shu, Haiyan Yu, Rongshan Huang, Haibin Agcy Sci Technol & Res Inst Infocomm Res Singapore 138632 Singapore

Linear prediction serves as a mathematical operation to estimate the future values of a discrete-time signal based on a linear function of previous samples. When applied to predictive coding of waveform such as speech and audio, a common issue that plagues compression performance is the non-stationary characteristics of prediction residuals around the starting point of the random access frames. This is because dependencies between prediction residuals and the historical waveform are interrupted to satisfy the random access requirement. In such cases, the dynamic range of the prediction residuals will fluctuate dramatically in such frames, leading to substantially poor coding performance in the subsequent entropy coder. In this study, the authors developed a solution to this long-standing issue by establishing a theoretical relationship between the energy envelope of linear prediction residuals in the random access frames and the prediction coefficients. Using the established relationship, an adaptive normalisation method is formulated as a preprocessor to the entropy coder to mitigate the poor coding performance in the random access frames. Simulation results confirm the superiority of the proposed method over existing solutions in terms of coding efficiency performance.

关键词： adaptive codes audio coding entropy codes speech coding optimal prediction residual normalisation predictive waveform coding random access frames linear prediction residuals mathematical operation future discrete-time signal value estimation speech coding audio coding subsequent entropy coder energy envelope adaptive normalisation method entropy coder poor coding performance mitigation

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Motion estimation and CABAC VLSI co-processors for real-time high-quality H.264/AVC video coding

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MICROPROCESSORS AND MICROSYSTEMS 2010年第7-8期34卷 316-328页

作者： Saponara, Sergio Martina, Maurizio Casula, Michele Fanucci, Luca Masera, Guido Univ Pisa Dept Informat Engn I-56122 Pisa Italy Politecn Torino Dept Elect I-1029 Turin Italy

Real-time and high-quality video coding is gaining a wide interest in the research and industrial community for different applications. H.264/AVC, a recent standard for high performance video coding, can be successfully exploited in several scenarios including digital video broadcasting, high-definition TV and DVD-based systems, which require to sustain up to tens of Mbits/s. To that purpose this paper proposes optimized architectures for H.264/AVC most critical tasks, Motion estimation and context adaptive binary arithmetic coding. Post synthesis results on sub-micron CMOS standard-cells technologies show that the proposed architectures can actually process in real-time 720 x 480 video sequences at 30 frames/s and grant more than 50 Mbits/s. The achieved circuit complexity and power consumption budgets are suitable for their integration in complex VLSI multimedia systems based either on AHB bus centric on-chip communication system or on novel Network-on-Chip (NoC) infrastructures for MPSoC (Multi-Processor System on Chip). (C) 2010 Elsevier B.V. All rights reserved.

关键词： Video coding Hardware architectures Motion estimation entropy coder Network-on-Chip VLSI multimedia systems

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Design of integrated multimedia compression and encryption systems

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IEEE TRANSACTIONS ON MULTIMEDIA 2005年第5期7卷 828-839页

作者： Wu, CP Kuo, CCJ Univ So Calif Dept Elect Engn Los Angeles CA 90089 USA Univ So Calif Integrated Media Syst Ctr Los Angeles CA 90089 USA

Two approaches for integrating encryption with multimedia compression systems are studied in this research, i.e., selective encryption and modified entropy coders with multiple statistical models. First, we examine the limitations of selective encryption using cryptanalysis, and provide examples that use selective encryption successfully. Two rules to determine whether selective encryption is suitable for a compression system are concluded. Next, we propose another approach that turns entropy coders into encryption ciphers using multiple statistical models. Two specific encryption schemes are obtained by applying this approach to the Huffman coder and the QM coder. It is shown that security is achieved without sacrificing the compression performance and the computational speed. This modified entropy coding methodology can be applied to most modern compressed audio/video such as MPEG audio, MPEG video, and JPEG/JPEG2000 images.

关键词： confidentiality CELP entropy coder G.723.1 speech coding Huffman coding multimedia encryption selective encryption signal scrambling QM coder

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Image compression by self-organized Kohonen map

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IEEE TRANSACTIONS ON NEURAL NETWORKS 1998年第3期9卷 503-507页

作者： Amerijckx, C Verleysen, M Thissen, P Legat, JD Univ Catholique Louvain Microelect Lab B-1348 Louvain Belgium VLSI Technol Sophia Antipolis France

This paper presents a compression scheme for digital still images, by using the Kohonen's neural network algorithm, not only for its vector quantization feature, but also for its topological property. This property allows an increase of about 80% for the compression rate. Compared to the JPEG standard, this compression scheme shows better performances (in terms of PSNR) for compression rates higher than 30.

关键词： discrete cosine transforms entropy coder image processing JPEG self-organizing feature maps variable length codes vector quantization

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