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2D-pattern matching image and video compression: Theory, algorithms, and experiments

IEEE TRANSACTIONS ON IMAGE PROCESSING 2002年第3期11卷 318-331页

作者： Alzina, M Szpankowski, W Grama, A Ecole Natl Super Telecommun Bretagne F-75013 Paris France Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA

In this paper, we propose a lossy data compression framework based on an approximate two-dimensional (2D) pattern matching (2D-PMC) extension of the Lempel-Ziv lossless scheme. This framework forms the basis upon which higher level schemes relying on differential coding, frequency domain techniques, prediction, and other methods can be built. We apply our pattern matching framework to image and video compression and report on theoretical and experimental results. Theoretically, we show that the fixed database model used for video compression leads to suboptimal but computationally efficient performance. The compression ratio of this model is shown to tend to the generalized entropy. For image compression, we use a growing database model for which we provide an approximate analysis. The implementation of 2D-PMC is a challenging problem from the algorithmic point of view. We use a range of techniques and data structures such as k-d trees, generalized run length coding, adaptive arithmetic coding, and variable and adaptive maximum distortion level to achieve good compression ratios at high compression speeds. We demonstrate bit rates in the range of 0.25-0.5 bpp for high-quality images and data rates in the range of 0.15-0.5 Mbps for a baseline video compression scheme that does not use any prediction or interpolation. We also demonstrate that this asymmetric compression scheme is capable of extremely fast decompression making it particularly suitable for networked multimedia applications.

关键词： approximate pattern matching arithmetic coding generalized run-length coding generalized Shannon entropy k-d trees Lempel-Ziv schemes multimedia compression rate distortion

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Efficient universal lossless data compression algorithms based on a greedy sequential grammar transform - Part two: With context models

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IEEE TRANSACTIONS ON INFORMATION THEORY 2003年第11期49卷 2874-2894页

作者： Yang, EH He, DK Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

The concept of context-free grammar (CFG)-based coding is extended to the case of countable-context models, yielding context-dependent grammar (CDG)-based coding. Given a countable-context model, a greedy CDG transform is proposed. Based on this greedy CDG transform, two universal lossless data compression algorithms, an improved sequential context-dependent algorithm and a hierarchical context-dependent algorithm, are then developed. It is shown that these algorithms are all universal in the sense that they can achieve asymptotically the entropy rate of any stationary, ergodic source with a finite alphabet. Moreover, it is proved that these algorithms' worst case redundancies among all individual sequences of length n from a finite alphabet are upper-bounded by d log log n/log n, as long as the number of distinct contexts grows with the sequence length n in the order of O(n(a)), where 0 < a < 1 and d are positive constants. It is further shown that for some nonstationary sources, the proposed context-dependent algorithms can achieve better expected redundancies than any existing CFG-based codes, including the Lempel-Ziv algorithm, the multilevel pattern matching algorithm, and the context-free algorithms in Part I of this series of papers.

关键词： arithmetic coding context models entropy grammar-based coding redundancy string and pattern matching universal data compression

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WORD-BASED TEXT COMPRESSION

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SOFTWARE-PRACTICE & EXPERIENCE 1989年第2期19卷 185-198页

作者： MOFFAT, A Department of Computer Science The University of Melbourne Parkville Victoria 3052 Australia

AbstractThe development of efficient algorithms to support arithmetic coding has meant that powerful models of text can now be used for data compression. Here the implementation of models based on recognizing and recording words is considered. Move‐to‐the‐front and several variable‐order Markov models have been tested with a number of different data structures, and first the decisions that went into the implementations are discussed and then experimental results are given that show English text being represented in under 2‐2 bits per character. Moreover the programs run at speeds comparable to other compression techniques, and are suited for prac

关键词： Data compression arithmetic coding Word‐based compression

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Improved Sequential MAP Estimation of CABAC Encoded Data with Objective Adjustment of the Complexity/Efficiency Tradeoff

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IEEE TRANSACTIONS ON COMMUNICATIONS 2009年第7期57卷 2014-2023页

作者： Jamaa, Salma Ben Kieffer, Michel Duhamel, Pierre Univ Paris Sud Supelec CNRS LSS F-91192 Gif Sur Yvette France

This paper presents an improved sequential MAP estimator to be used as a joint source-channel decoding technique for CABAC encoded data. The decoding process is compatible with realistic implementations of CABAC in standards like H.264, Le, handling adaptive probabilities, context modeling and integer arithmetic coding. Soft-input decoding is obtained using an improved sequential decoding technique, which allows to obtain a tradeoff between complexity and efficiency. The algorithms are simulated in a context reminiscent of H264. Error detection is realized by exploiting on one side the properties of the binarization scheme and on the other side the redundancy left in the code string. As a result, the CABAC compression efficiency is preserved and no additional redundancy is introduced in the bit stream. Simulation results outline the efficiency of the proposed techniques for encoded data sent over AWGN and UMTS-OFDM channels.

关键词： arithmetic coding joint source-channel decoding MAP estimation sequential decoding

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A high-performance JPEG2000 architecture

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2003年第3期13卷 209-218页

作者： Andra, K Chakrabarti, C Acharya, T Arizona State Univ Dept Elect Engn Res Ctr Tempe AZ 85287 USA

JPEG2000 is an upcoming compression standard for still images that has a feature set well tuned for diverse data dissemination. These features are possible due to adaptation of the discrete wavelet transform, intra-subband bit-plane,coding, and binary arithmetic coding in the standard. In this paper, we propose a system-level architecture capable of encoding and decoding the JPEG2000 core algorithm that has been defined in Part I of the standard. The key components include dedicated architectures for wavelet, bit plane, and arithmetic coders and memory interfacing between the coders. The system architecture has been implemented in VHDL and its performance evaluated for a set of images. The estimated area of the architecture, in 0.18-mu technology, is 3-min square and the estimated frequency of operation is 200 MHz.

关键词： binary arithmetic coding bit-plane coding JPEG2000 system architecture wavelet transform

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Microarray Image Lossless Compression Using General Entropy Coders and Image Compression Standards

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2023年第8期42卷 5013-5040页

作者： Joseph, Steffy Maria Sathidevi, P. S. Natl Inst Technol Elect & Commun Dept Calicut 673601 Kerala India

Lossless compression is still a challenging task in the case of microarray images. This research proposes two algorithms that aim to improve the lossless compression efficiency for high spatial resolution microarray images using general entropy codecs, namely Huffman and arithmetic coders and the image compression standard JPEG 2000. Using the standards ensures that decoders are available to reassess the images for future applications. Typically, microarray images have a bit-depth of 16. In proposed algorithm 1, every image's per bit-plane entropy profile is calculated to automatically determine a better threshold T to split the bit-planes into the foreground and background sub-images. T is initially set to 8. However, in algorithm 1, T is updated, balancing the average value of per bit-plane entropies of the segmented sub-images of an image for improved lossless compression results. Codecs are applied individually to the produced sub-images. Proposed algorithm 2 is designed to increase the lossless compression efficiency of any unmodified JPEG 2000-compliant encoder while reducing side information overhead. In this, pixel intensity reindexing and, thereby, changing the histograms of the same segmented sub-images obtained from algorithm 1 are implemented and confirmed to get better JPEG 2000 results in lossless mode than applying it to the original image. The lossless JPEG 2000 compression performance on microarray images is also compared to JPEG-LS in particular. The experiments are carried out to validate the methods on seven benchmark datasets, namely ApoA1, ISREC, Stanford, MicroZip, GEO, Arizona, and IBB. The average first-order entropy of the datasets above is calculated and compared for codecs and better than competitive efforts in the literature.

关键词： arithmetic coding Entropy Huffman coding JPEG 2000 Lossless compression Microarray images Pixel intensity reindexing Splitting bit-planes

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Silhouette 4D With Context Selection: Lossless Geometry Compression of Dynamic Point Clouds

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IEEE SIGNAL PROCESSING LETTERS 2021年 28卷 1660-1664页

作者： Ramalho, Evaristo Peixoto, Eduardo Medeiros, Edil Univ Brasilia Dept Elect Engn BR-70910900 Brasilia DF Brazil

Recently we have proposed a coding algorithm of point cloud geometry based on a rather different approach from the popular octree representation. In our algorithm, the point cloud is decomposed in silhouettes, hence the name Silhouette Coder, and context adaptive arithmetic coding is used to exploit redundancies within the point cloud (intra frame coding), and also using a reference point cloud (inter frame coding). In this letter we build on our previous work and propose a context selection algorithm as a pre-processing stage. With this algorithm, the point cloud is first parsed testing a large number of candidate context locations. The algorithm selects a small number of these contexts that better reflect the current point cloud, and then encode it with this choice. The proposed method further improves the results of our previous coder, Silhouette 4D, by 10%, on average, on a dynamic point cloud dataset of the JPEG Pleno, and achieves bitrates competitive with some high quality lossy coders such as the MPEG G-PCC.

关键词： Three-dimensional displays Image coding Encoding Transform coding Signal processing algorithms Codecs Geometry Point clouds inter coder lossless coding arithmetic coding

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Fuzzy-Coded Space-Frequency Quantization for SAR Data Compression

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IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 2004年第2期1卷 90-93页

作者： Gleich, Dusan Gergic, Bojan Cucej, Zarko Planinsic, Peter Univ Maribor Fac Elect Engn & Comp Sci SLO-2000 Maribor Slovenia

In this letter, we propose a new image coding technique, which is a combination of space frequency quantization and a context-based modeling using fuzzy logic. The compression results showed that the proposed coder outperforms the state-of-the-art coders in the rate-distortion sense for compression of processed synthetic aperture radar amplitude data.

关键词： arithmetic coding context modeling fuzzy logic trellis-coded quantization wavelet transformation

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Quantitative performance evaluation of the lossless compression approach using pole-zero modeling

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2000年第1期38卷 39-43页

作者： Nijim, YW Stearns, SD Mikhael, WB Thomson Consumer Elect Indianapolis IN 46290 USA Sandia Natl Labs Albuquerque NM 87106 USA Univ Cent Florida Dept Elect & Comp Engn Orlando FL 32816 USA

A technique for lossless compression of seismic signals is proposed. The algorithm employed is based on the equation-error structure, which approximates the signal by minimizing the error in the least-square sense and estimates the transfer characteristic as a rational function or equivalently, as an autoregressive moving average process. The algorithm is implemented in the frequency domain. The performance of the proposed technique is compared with the lossless linear predictor and the differentiator approaches for compressing seismic signals, The residual sequence of these schemes is coded using arithmetic coding. The suggested approach yields compression measures (in terms of bits per sample) lower than the lossless linear predictor and the differentiator for compressing different classes of seismic signals.

关键词： arithmetic coding data compression lossless compression signal modeling

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High-throughput CABAC codec architecture for HEVC

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ELECTRONICS LETTERS 2013年第18期49卷 1145-1146页

作者： Choi, Yongseok Choi, Jongbum Samsung Elect Multimedia R&D Team DMC R&D Ctr Suwon South Korea

A VLSI architecture of a context adaptive binary arithmetic coding (CABAC) entropy codec for high-efficiency video coding (HEVC), the next generation video coding standard, is presented and analysis of its performance in terms of effective processing throughput, i.e. bin/s, is provided. For high throughput, the architecture is designed to process up to two regular bins per unit time while minimising pipeline stall due to inherent dependencies of CABAC through various optimisations including context forwarding and speculative decoding. The experiments show that the effective throughput is achieved up to 1.60 bins or 1.41 bits per cycle, which corresponds to 469.5 Mbit/s at the operating frequency of 333 MHz, under practical video coding environments.

关键词： MATHEMATICAL programming arithmetic coding FUNCTIONAL equations -- Numerical solutions BINARY codes coding theory VIDEO coding (Computer science)

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