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International Conference on Audio, Language and Image Processing (ICALIP)

作者： Jiang, Xiaobo Song, Bo Zhuang, Xinhua Univ Missouri Dept Elect Engn & Comp Sci Columbia MO 65211 USA

ISBN: (纸本)9781538651957

High-resolution image compression remains a hot research topic today due to the widespread use of high-definition displays in computers and mobile devices. Conventionally, there are two distinct categories in image compression: 1) Subband coding based on multi-level discrete wavelet transform (DWT);2) Hybrid coding based on block prediction and discrete cosine transform (DCT). Wavelet image compression has delivered a much higher coding gain over the classical DCT-based JPEG. More recently, through using a delicate yet innovative block prediction scheme before DCT, HEVC Intra coding has delivered an impressive coding gain over JPEG 2000, where the coding gain is measured by the peak signal-to-noise ratio (PSNR) gain at the same bit rate. However, it is hard to integrate a block prediction scheme with wavelet transform. A block prediction error image could be statistically quite different from an ordinary image. In the paper, we focus on developing a wavelet image coder SLCCA Plus, which is a much-enhanced version of SLCCA. The enhancement involves quantization, cluster filtering, shared-boundary-zero handling and context model design for adaptive arithmetic coding. The experiments on standard images of 512x512 are conducted to compare the proposed SLCCA Plus to JPEG 2000 and SLCCA. On average, SLCCA Plus achieves 7% bit saving over JPEG 2000 and 4% over SLCCA.

关键词： image coding discrete wavelet transform SLCCA cluster quantization context-based arithmetic coding

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Progressive 3D mesh compression using MOG-based Bayesian entropy coding and gradual prediction

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VISUAL COMPUTER 2014年第10期30卷 1077-1091页

作者： Lee, Dae-Youn Sull, Sanghoon Kim, Chang-Su Korea Univ Sch Elect Engn Seoul South Korea

A progressive 3D triangular mesh compression algorithm built on the MOG-based Bayesian entropy coding and the gradual prediction scheme is proposed in this work. For connectivity coding, we employ MOG models to estimate the posterior probabilities of topology symbols given vertex geometries. Then, we encode the topology symbols using an arithmetic coder with different contexts, which depend on the posterior probabilities. For geometry coding, we propose the gradual prediction labeling and the dual-ring prediction to divide vertices into groups and predict later groups more efficiently using the information in already encoded groups. Simulation results demonstrate that the proposed algorithm provides significantly better performance than the conventional wavemesh coder, with the average bit rate reduction of about 16.9 %.

关键词： Triangular mesh 3D mesh compression Predictive coding Progressive coding Mixture of Gaussian model context-based arithmetic coding

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arithmetic coding for image compression with adaptive weight-context classification

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2013年第7期28卷 727-735页

作者： Wu, Jiaji Xu, Zhenzhen Jeon, Gwanggil Zhang, Xiangrong Jiao, Licheng Xidian Univ Minist Educ China Key Lab Intelligent Percept & Image Understanding Xian 710071 Peoples R China Incheon Natl Univ Dept Embedded Syst Engn Inchon 406772 South Korea

In this paper, a new binary arithmetic coding strategy with adaptive-weight context classification is introduced to solve the context dilution and context quantization problems for bitplane coding. In our method, the weight, obtained using a regressive-prediction algorithm, represents the degree of importance of the current coefficient/block in the wavelet transform domain. Regarding the weights as contexts, the coder reduces the context number by classifying the weights using the Lloyd Max algorithm, such that high-order is approximated as low-order context arithmetic coding. The experimental results show that our method effectively improves the arithmetic coding performance and outperforms the compression performances of SPECK, SPIHT and JPEG2000. (C) 2013 Elsevier B.V. All rights reserved.

关键词： context-based arithmetic coding Adaptive Regressive-prediction Weight context classification

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Lossless Compression of Hyperspectral Images Using Adaptive Prediction and Backward Search Schemes

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JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 2011年第2期27卷 419-435页

作者： Lin, Cheng-Chen Hwang, Yin-Tsung Natl Chung Hsing Univ Dept Elect Engn Taichung 402 Taiwan

In this paper, an effective lossless compression scheme for hyperspectral images is presented. The proposed scheme is based on a table look-up approach in prediction and employs two novel measures to improve the compression performance. The first measure takes advantage of the spatial data correlation and formulates the derivation of a spectral domain predictor as a process of Wiener filtering. The derived predictor is considered statistically optimal provided that the data within a small context window are stationary. This property holds in most cases due to spatial data correlation. Under the Wiener filtering framework, the proposed predictor can be extended from one-tap to multi-tap prediction to further improve performance. In the second measure, a backward search scheme is used instead of look-up tables, which reduces the memory storage requirement drastically and achieves performance equivalent to that obtained using multiple look-up tables. The search effort is greatly reduced using the quantization index approach. Simulations on parameter settings and refinements on entropy coding are conducted to fine-tune performance. Experiments on 5 sequences of AVIRIS images show that the proposed scheme can yield an average compression ratio of as high as 3.85.

关键词： hyperspectral imaging lossless compression adaptive prediction wiener filtering context-based arithmetic coding

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A comparative study of image compression based on directional wavelets

A comparative study of image compression based on directiona...

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Conference on Visual Communications and Image Processing 2007

作者： Li, Kun Xu, Wenli Dai, Qionghai Wang, Yao Tsinghua Univ Dept Automat Beijing 100084 Peoples R China Polytech Univ Elect & Comp Engn Dept Brooklyn NY 11201 USA

ISBN: (纸本)9780819466211

Discrete wavelet transform is an effective tool to generate scalable stream, but it cannot efficiently represent edges which are not aligned in horizontal or vertical directions, while natural images often contain rich edges and textures of this kind. Hence, recently, intensive research has been focused particularly on the directional wavelets which can effectively represent directional attributes of images. Specifically, there are two categories of directional wavelets: redundant wavelets (RW) and adaptive directional wavelets (ADW). One representative redundant wavelet is the dual-tree discrete wavelet transform (DDWT), while adaptive directional wavelets can be further categorized into two types: with or without side information. In this paper, we briefly introduce directional wavelets and compare their directional bases and image compression performances.

关键词： scalable image coding discrete wavelet transform directional wavelets redundant wavelets dual-tree discrete wavelet transform adaptive directional wavelets side information basis functions compression performances context-based arithmetic coding

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Mutual information-based analysis of JPEG2000 contexts

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2005年第4期14卷 411-422页

作者： Liu, Z Karam, LJ Qualcomm Inc San Diego CA 92121 USA Arizona State Univ Dept Elect Engn Tempe AZ 85287 USA

context-based arithmetic coding has been widely adopted in image and video compression and is a key component of the new JPEG2000 image compression standard. In this paper, the contexts used in JPEG2000 are analyzed using the mutual information, which is closely related to the compression performance. We first show that, when combining the contexts, the mutual information between the contexts and the encoded data will decrease unless the conditional probability distributions of the combined contexts are the same. Given I, the initial number of contexts, and F, the final desired number of contexts, there are S(I, F) possible context classification schemes where S(I, F) is called the Stirling number of the second kind. The optimal classification scheme is the one that gives the maximum mutual information. Instead of using an exhaustive search, the optimal classification scheme can be obtained through a modified generalized Lloyd algorithm with the relative entropy as the distortion metric. For binary arithmetic coding, the search complexity can be reduced by using dynamic programming. Our experimental results show that the JPEG2000 contexts capture the correlations among the wavelet coefficients very well. At the same time, the number of contexts used as part of the standard can be reduced without loss in the coding performance.

关键词： context-based arithmetic coding JPEG2000 mutual information

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Low memory, low complexity line-based wavelet image compression

Low memory, low complexity line-based wavelet image compress...

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7th International Conference on Signal Processing

作者： Zhang, HW Liu, ZG Chen, HX Tianjin Univ Sch Elect Engn & Automat Tianjin 300072 Peoples R China

ISBN: (纸本)7121002159

Due to the large requirement for memory and the high complexity of computation, JPEG2000 cannot be used in many conditions especially in the memory, constraint equipment The line-based wavelet transform was proposed and accepted because lower memory is required without affecting the result of wavelet transform. In this paper, the improved lifting scheme is introduced to perform wavelet transform to replace Mallat method that is used in the original line-based wavelet transform. The three-adder unit is adopted to realize lifting scheme. The corresponding context-based arithmetic coding is designed here so that the proposed algorithm is more suitable for equipment.

关键词： line-based wavelet transform lifting scheme three-adder unit context-based arithmetic coding

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Novel efficient architecture for JPEG2000 entropy coder

Novel efficient architecture for JPEG2000 entropy coder

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Conference on Visual Communications and Image Processing 2003

作者： Fatemi, O Asadzadeh, P Univ Teheran Dept Elect & Comp Engn Tehran Iran

ISBN: (纸本)0819450235

With the continual expansion of multimedia and Internet applications, the needs and requirements of advanced technologies, grew and evolved. With the increasing use of multimedia technologies, image compression techniques require higher performance as well as new features. Significant progress has recently been made in image compression techniques using discrete wavelet transforms. The overall performance of these schemes may be further improved by properly designing of efficient entropy coders. In this paper, we describe an efficient architecture for JPEG2000 entropy coder, which is a new standard to address the needs in the specific area of still image encoding. Our proposed architecture consists of two main parts, the coefficient bit modeler (CBM) and the binary arithmetic coder (BAC), which communicate through a FIFO buffer. Optimizations have been made in our proposed architecture to reduce accesses to memories. Our Proposed architecture is fast and modular and is suitable for real-time applications.

关键词： JPEG2000 context-based arithmetic coding coefficient bit modeler CBM bit plane coder BPC binary arithmetic coder BAC

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