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IEEE International Conference on Image Processing

作者： Min Gao Debin Zhao Qiang Wang Wen Gao Department of Computer Science and Technology Harbin Institute of Technology

ISBN: (纸本)9781479957521

This paper presents an arithmetic coding scheme for DCT coefficients in video compression, in which the number of non-zero coefficients, significant map and level information for a DCT block are used as coding elements. To exploit the statistical correlations, an hierarchical dependency context model (HDCM) is proposed, where the number of non-zero coefficients and scanned position are used to capture the magnitude varying tendency of DCT coefficients. Then a new binary arithmetic coding using HDCM (HDCMBAC) is proposed to code the coding elements. Experimental results demonstrate that HDCMBAC can achieve the similar coding performance as CABAC at low and high QPs. Meanwhile the context modeling and arithmetic decoding in HDCMBAC can be carried out in parallel, since the context dependency only exists among different parts of basic coding elements in HDCM.

关键词： arithmetic coding Context modeling Video compression DCT coefficients

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MASSIVELY PARALLEL LOSSLESS COMPRESSION OF MEDICAL IMAGES USING LEAST-SQUARES PREDICTION AND arithmetic coding

MASSIVELY PARALLEL LOSSLESS COMPRESSION OF MEDICAL IMAGES US...

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IEEE International Conference on Image Processing

作者： Andreas Weinlich Johannes Rehm Peter Amon Andreas Hutter André Kaup Multimedia Communications and Signal Processing Universit?t Erlangen-Nürnberg Erlangen Germany Imaging and Computer Vision Siemens Corporate Technology Munich Germany

ISBN: (纸本)9781479923427

Medical imaging in hospitals requires fast and efficient image compression to support the clinical work flow and to save costs. Least-squares autoregressive pixel prediction methods combined with arithmetic coding constitutes the state of the art in lossless image compression. However, a high computational complexity of both prevents the application of respective CPU implementations in practice. We present a massively parallel compression system for medical volume images which runs on graphics cards. Image blocks are processed independently by separate processing threads. After pixel prediction with specialized border treatment, prediction errors are entropy coded with an adaptive binary arithmetic coder. Both steps are designed to match particular demands of the parallel hardware architecture. Comparisons with current image and video coders show efficiency gains of 3.3-13.6% while compression times can be reduced to a few seconds.

关键词： Nvidia CUDA GPGPU parallelization adaptive binary arithmetic coding parallel predictive coding 2-D least-squares autoregression computed tomography Medical imaging Workflow X-Ray Computed Tomography arithmetic Data compression Image compression images state of the art video coder lossless compression lossless image compression arithmetic coding Current Pick compression system graphic images

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AN FPGA-BASED FAST TWO-SYMBOL PROCESSING ARCHITECTURE FOR JPEG 2000 arithmetic coding

AN FPGA-BASED FAST TWO-SYMBOL PROCESSING ARCHITECTURE FOR JP...

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Nandini Ramesh Kumar Wei Xiang Yafeng Wang University of Southern Queensland Toowoomba QLD AUSTRALIA Beijing University of Posts and Telecommunications Beijing CHINA

ISBN: (纸本)9781424442959

In this paper, a field-programmable gate array (FPGA) based enhanced architecture of the arithmetic coder is proposed, which processes two symbols per clock cycle as compared to the conventional architecture that processes only one symbol per clock. The input to the arithmetic coder is from the bit-plane coder, which generates more than two context-decision pairs per clock cycle. But due to the slow processing speed of the arithmetic coder, the overall encoding becomes slow. Hence, to overcome this bottleneck and speed up the process, a two-symbol architecture is proposed which not only doubles the throughput, but also can be operated at frequencies greater than 100 MHz. This architecture achieves a throughput of 210 Msymbols/sec and the critical path is at 9.457 ns.

关键词： arithmetic coding JPEG 2000 FPGA Two-symbol architecture EBCOT

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ADAPTIVE-DISTRIBUTED arithmetic coding FOR LOSSLESS COMPRESSION

ADAPTIVE-DISTRIBUTED ARITHMETIC CODING FOR LOSSLESS COMPRESS...

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2010 2nd IEEE International Conference on Network Infrasturcture & Digital Content(2010年第二届IEEE网络基础设施与数字内容国际会议 IC-NIDC 2010)

作者： Jechang Jeong Jiaji Wu Licheng Jiao Minli Wang Department of Electronics and Computer Engineering Hanyang University Seoul 133-791 Korea School of Electronic Engineering Xidian University Xi’an 710071 China

Distributed arithmetic coding (DAC) is an effective implementation of Slepian–Wolf coding (SWC), especially for short data blocks. However, currently, most of the DAC research methods focus on the lossy compression on the condition that the prior knowledge is known in advance. In order to realize lossless and adaptive compression, in this paper, we propose lossless adaptivedistributed arithmetic coding (LADAC) using the method of EOF (end of the file) and the adaptive encoding. In our proposed LADAC, encoder and decoder can work simultaneously instead of alternatively, and encoder-driven method is also achieved without a feedback channel instead of decoder-driven. Experimental results show that LADAC performs the better compression performance and the lower complexity than conventional lossless distributed arithmetic coding (LDAC).

关键词： Distributed source coding arithmetic coding Slepian-Wolf coding Wyner-Ziv coding compression.

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AN EFFICIENT ADAPTIVE arithmetic coding FOR BLOCK-BASED LOSSLESS IMAGE COMPRESSION USING MIXTURE MODELS

AN EFFICIENT ADAPTIVE ARITHMETIC CODING FOR BLOCK-BASED LOSS...

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IEEE International Conference on Image Processing

作者： Atef MASMOUDI Afif MASMOUDI William PUECH Sfax Preparatory Engineering Institute University of Sfax LIRMM UMR CNRS 5506 University of Montpellier II

ISBN: (纸本)9781479957521

In this paper, we investigate finite mixture models (FMM) and adaptive arithmetic coding (AAC) for block-based lossless image compression. The AAC performance depends on how well the model fits the source symbols' statistics. In addition, when encoding small block, the number of source symbols is considerably large by comparison with the number of samples in that block, which results in a loss of compression efficiency. To this end, we propose to model each block with an appropriately FMM by maximizing the probability of samples that belong to that block. The mixture parameters are estimated through maximum likelihood using the Expectation-Maximization (EM) algorithm in order to maximize the arithmetic coding efficiency. The comparative studies of some particular test images prove the efficiency of the mixture models for lossless image compression. The experimental results show significant improvements over conventional adaptive arithmetic encoders and the state-of-the-art lossless image compression standards and algorithms.

关键词： arithmetic coding Finite mixture models Lossless image compression Expectation-Maximization algorithm

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The design of an adaptive on-line binary arithmetic-coding chip

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND APPLICATIONS 1998年第7期45卷 693-706页

作者： Kuang, SR Jou, JM Chen, YL Natl Cheng Kung Univ Dept Elect Engn Tainan 70101 Taiwan

In this paper, we present a very large scale integration (VLSI) design of the adaptive binary arithmetic coding for lossless data compression and decompression. The main modules of it consist of an adaptive probability estimation modeler (APEM), an arithmetic operation unit (AOU), and a normalization unit (NU), A new bit-stuffing technique, which simultaneously solves both the carry-over and source-termination problems efficiently, is proposed and designed in an NU, The APEM estimates the conditional probabilities of input symbols efficiently using a table lookup approach with 1.28-kbytes memory. A new formula which efficiently reflects the change of symbols' occurring probability is proposed, and a complete binary tree is used to set up the values in the probability table of an APEM, In an AOU, a simplified parallel multiplier, which requires approximately half of the area of a standard parallel multiplier while maintaining a good compression ratio, is proposed. Owing to these novel designs, the designed chip can compress any type of data with an efficient compression ratio. An asynchronous interface circuit with an 8-b first-in first-out (FIFO) buffer for input/output (I/O) communication of the chip is also designed. Thus, both I/O and compression operations in the chip can be done simultaneously. Moreover, the concept of design for testability is used and a scan path is implemented in the chip. A prototype 0.8-mu m chip has been designed and fabricated in a reasonable die size. This chip can yield a processing rate of 3 Mb/s with a clock rate of 25 MHz.

关键词： arithmetic coding chip design lossless data compression

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HIGH CAPACITY DATA-HIDING FOR 3D MESHES BASED ON STATIC arithmetic coding

HIGH CAPACITY DATA-HIDING FOR 3D MESHES BASED ON STATIC ARIT...

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IEEE International Conference on Image Processing

作者： V. Itier W. Puech J. P. Pedeboy LIRMM UMR 5506 CNRS University of Montpellier STRATEGIES S.A.

ISBN: (纸本)9781479983407

3D meshes are widely used today in very different domains for example;game, medical diagnostic, CAD (computed aided design) or more recently 3-D printing. In this paper, we provide a new data hiding method that has a huge capacity, cp = 3c(n - 1), where n is the vertex number of the mesh and c is an integer. The proposed method consists to compute a Hamiltonian path along the mesh as synchronization. At each step of path building, 3c bits are embedded. The embedding is designed to be a distance relation between a vertex and its father in the path. Moreover, the method uses static arithmetic coding to embed message information. We analyzed the proposed method by inserting RGB images in 3D meshes.

关键词： 3D data hiding High capacity Geometry synchronization HIGH CAPACITY Mesh Hamiltonian path embedding arithmetic arithmetic coding Fathers Meshes Printing, Three-Dimensional corners vertex head new data

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arithmetic EDGE coding FOR ARBITRARILY SHAPED SUB-BLOCK MOTION PREDICTION IN DEPTH VIDEO COMPRESSION

ARITHMETIC EDGE CODING FOR ARBITRARILY SHAPED SUB-BLOCK MOTI...

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19th IEEE International Conference on Image Processing (ICIP)

作者： Daribo, Ismael Cheung, Gene Florencio, Dinei National Institute of Informatics Japan Microsoft Research United States

ISBN: (纸本)9781467325332;9781467325349

Depth map compression is important for compact representation of 3D visual data in "texture-plus-depth" format, where texture and depth maps of multiple closely spaced viewpoints are encoded and transmitted. A decoder can then freely synthesize any chosen intermediate view via depth-image-based rendering (DIBR) using neighboring coded texture and depth maps as anchors. In this work, we leverage on the observation that "pixels of similar depth have similar motion" to efficiently encode depth video. Specifically, we divide a depth block containing two zones of distinct values (e. g., foreground and background) into two sub-blocks along the dividing edge before performing separate motion prediction. While doing such arbitrarily shaped sub-block motion prediction can lead to very small prediction residuals (resulting in few bits required to code them), it incurs an overhead to losslessly encode dividing edges for sub-block identification. To minimize this overhead, we first devise an edge prediction scheme based on linear regression to predict the next edge direction in a contiguous contour. From the predicted edge direction, we assign probabilities to each possible edge direction using the von Mises distribution, which are subsequently inputted to a conditional arithmetic codec for entropy coding. Experimental results show an average overall bitrate reduction of up to 30% over classical H.264 implementation.

关键词： Depth-image-based rendering depth map coding arithmetic coding edge coding

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A novel secure arithmetic image coding algorithm based on Two-dimension Generalized Logistic Mapping 5

A novel secure arithmetic image coding algorithm based on Tw...

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Fifth International Conference on Instrumentation & Measurement, Computer, Communication, and Control (IMCCC)

作者： Liu Huiying Xu Caiyun Kong jun Du Ying Armored Force Inst Bengbu Peoples R China

ISBN: (纸本)9781467377232

a novel secure arithmetic image coding algorithm based on Two-dimensional Generalized Logistic Mapping is proposed. Firstly, according to the digital image size mxn, two 2D chaotic sequences are generated by logistic chaotic mapping. Then, the original image data is scrambled by sorting the chaotic sequence. Secondly, the chaotic sequence is optimized to generate key stream which is used to mask the image data. Finally, to generate the final output, the coding interval order is controlled by the chaotic sequence during the arithmetic coding process. Experiment results show the proposed secure algorithm has good robustness and can be applied in the arithmetic coder for multimedia such as video and audio with little loss of coding efficiency.

关键词： arithmetic coding image encryption multimedia data two-dimensional generalized logistic mapping

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An Improved arithmetic coding Algorithm

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Journal of Shanghai University(English Edition) 2004年第4期8卷 455-458页

作者：海梅张建军倪兴芳 Department of Mathematics College of Sciences Shanghai University Shanghai 200436 P.R.China Department of Electronic Engineering College of Technology Shanghai Jiaotong University Shanghai 200030 P.R.China

arithmetic coding is the most powerful technique for statiscal lossless encoding that has attracted much attention in recent years. In this paper, we presents a new implementation of bit-level arithmetic coding by use of integer additions and shifts. The new algorithm has less computation complexity and is more flexible to use, and thus is very suitable for software and hardware design. We also discuss the application of the algorithm to the data encryption.

关键词： arithmetic coding data encryption.

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