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PCA-lbg-based algorithms for VQ codebook generation

INTERNATIONAL JOURNAL OF ELECTRONICS 2015年第4期102卷 529-547页

作者： Tsai, Jinn-Tsong Yang, Po-Yuan Natl Pingtung Univ Educ Dept Comp Sci Pingtung 900 Taiwan

Vector quantisation (VQ) codebooks are generated by combining principal component analysis (PCA) algorithms with Linde-Buzo-Gray (lbg) algorithms. All training vectors are grouped according to the projected values of the principal components. The PCA-lbg-based algorithms include (1) PCA-lbg-Median, which selects the median vector of each group, (2) PCA-lbg-Centroid, which adopts the centroid vector of each group, and (3) PCA-lbg-Random, which randomly selects a vector of each group. The lbg algorithm finds a codebook based on the better vectors sent to an initial codebook by the PCA. The PCA performs an orthogonal transformation to convert a set of potentially correlated variables into a set of variables that are not linearly correlated. Because the orthogonal transformation efficiently distinguishes test image vectors, the proposed PCA-lbg-based algorithm is expected to outperform conventional algorithms in designing VQ codebooks. The experimental results confirm that the proposed PCA-lbg-based algorithms indeed obtain better results compared to existing methods reported in the literature.

关键词： vector quantisation codebook generation principal component analysis lbg algorithm

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Performance comparisons between PCA-EA-lbg and PCA-lbg-EA approaches in VQ codebook generation for image compression

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INTERNATIONAL JOURNAL OF ELECTRONICS 2015年第11期102卷 1831-1851页

作者： Tsai, Jinn-Tsong Chou, Ping-Yi Chou, Jyh-Horng Natl Pingtung Univ Dept Comp Sci Pingtung 900 Taiwan Natl Kaohsiung First Univ Sci & Technol Inst Engn Sci & Technol Kaohsiung 824 Taiwan

The aim of this study is to generate vector quantisation (VQ) codebooks by integrating principle component analysis (PCA) algorithm, Linde-Buzo-Gray (lbg) algorithm, and evolutionary algorithms (EAs). The EAs include genetic algorithm (GA), particle swarm optimisation (PSO), honey bee mating optimisation (HBMO), and firefly algorithm (FF). The study is to provide performance comparisons between PCA-EA-lbg and PCA-lbg-EA approaches. The PCA-EA-lbg approaches contain PCA-GA-lbg, PCA-PSO-lbg, PCA-HBMO-lbg, and PCA-FF-lbg, while the PCA-lbg-EA approaches contain PCA-lbg, PCA-lbg-GA, PCA-lbg-PSO, PCA-lbg-HBMO, and PCA-lbg-FF. All training vectors of test images are grouped according to PCA. The PCA-EA-lbg used the vectors grouped by PCA as initial individuals, and the best solution gained by the EAs was given for lbg to discover a codebook. The PCA-lbg approach is to use the PCA to select vectors as initial individuals for lbg to find a codebook. The PCA-lbg-EA used the final result of PCA-lbg as an initial individual for EAs to find a codebook. The search schemes in PCA-EA-lbg first used global search and then applied local search skill, while in PCA-lbg-EA first used local search and then employed global search skill. The results verify that the PCA-EA-lbg indeed gain superior results compared to the PCA-lbg-EA, because the PCA-EA-lbg explores a global area to find a solution, and then exploits a better one from the local area of the solution. Furthermore the proposed PCA-EA-lbg approaches in designing VQ codebooks outperform existing approaches shown in the literature.

关键词： vector quantisation codebook generation principle component analysis lbg algorithm evolutionary algorithms

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Improved PSO-lbg to Design VQ Codebook

Improved PSO-LBG to Design VQ Codebook

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SICE Annual Conference

作者： Chou, Ping-Yi Tsai, Jinn-Tsong Chou, Jyh-Horng Ho, Wen-Hsien Shi, Hon-Yi Chen, Shinn-Horng Natl Kaohsiung First Univ Sci & Technol Inst Syst Informat & Control Kaohsiung Taiwan Natl Pingtung Univ Educ Dept Comp Sci Pingtung Taiwan Natl Kaohsiung Univ Appl Sci Dept Elect Engn Kaohsiung 807 Taiwan Kaohsiung Med Univ Dept Healthcare Adm & Med Informat Kaohsiung Taiwan Natl Kaohsiung Univ Appl Sci Dept Mech Engn Kaohsiung 807 Taiwan

ISBN: (纸本)9784907764432

The purpose of this study is to improve the Linde-Buzo-Gray (lbg) algorithm by using improved particle swarm optimization (IPSO) to generate vector quantization (VQ) codebooks. The proposed IPSO-lbg algorithm improves PSO-lbg in terms of initial particles and evolution function. The IPSO generates better initial particles by grouping the original blocks and expands search area by dynamically adjusting the individual coefficient, social coefficient, and weight value of the evolution function. Then, the best solution obtained by the IPSO is provided for a lbg to find a codebook. Therefore, the proposed IPSO-lbg is well enhanced on search space and convergence. The experiment results confirm that the proposed IPSO-lbg find better codebooks than existing methods reported in the literatures.

关键词： Vector quantization image compression PSO algorithm lbg algorithm

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A new method of data compression using wavelet tree structure and improved lbg

A new method of data compression using wavelet tree structur...

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International Computer Conference on Wavelet Active Media Technology and Information Processing

作者： Yu Xiaohong Yu Wenfang Ma Yingxiao Zhejiang Gongshuang Univ Coll Comp & Informat Hangzhou 310035 Peoples R China

ISBN: (纸本)9812700420

In this paper, an efficient data compression scheme using wavelet tree structure and improved lbg algorithm is proposed. First, the image is decomposition by wavelet transform with selected wavelet basis. Second, the wavelet tree structure can be made of the decorrelation coefficient. In general, we use the traditional training algorithm for vector quantization such as the lbg algorithm, here, we presented a novel training algorithm for vector quantization in which the convergence of the entropy sequence of each region sequence is used as the condition of the end of the algorithm. Compared with the lbg algorithm, it is simple, fast and easy to be controlled. Finally, We test the performance of the algorithm by image Lena. The result shows they can obtain the better compression rate, but the running time of it is at most one second of lbg.

关键词： wavelet transform wavelet tree structure vector quantization lbg algorithm entropy

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FAST algorithm FOR VQ CODEBOOK DESIGN

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IEE PROCEEDINGS-I COMMUNICATIONS SPEECH AND VISION 1991年第5期138卷 357-362页

作者： CHEN, SH HSIEH, WM Department of Communication Engineering National Chiao Tung University Hsinchu Republic of China

The paper presents a fast codebook training algorithm for vector quantisation. It uses an elimination rule, based on triangular inequality criteria, as well as the partial distortion elimination method, to relieve the computational burden of a conventional codebook training algorithm, including a binary codeword splitting algorithm for the initial codebook and the lbg recursive algorithm. Over 95% savings in both multiplication and addition operations were achieved in the simulation of a VQ codebook training of a 'Lena' image using 16-dimensional vectors.

关键词： BINARY CODEWORD SPLITTING IMAGE CODING lbg algorithm VECTOR QUANTIZATION

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FIVQ algorithm for interference hyper-spectral image compression

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OPTICS COMMUNICATIONS 2014年 322卷 97-104页

作者： Wen, Jia Ma, Caiwen Zhao, Junsuo Chinese Acad Sci Sci Integrated Informat Syst Lab Inst Software Beijing 100190 Peoples R China Chinese Acad Sci Xian Inst Opt & Precis Mech Xian 710119 Shaanxi Peoples R China

Based on the improved vector quantization (IVQ) algorithm [1] which was proposed in 2012, this paper proposes a further improved vector quantization (FIVQ) algorithm for LASIS (Large Aperture Static Imaging Spectrometer) interference hyper-spectral image compression. To get better image quality, IVQ algorithm takes both the mean values and the VQ indices as the encoding rules. Although IVQ algorithm can improve both the bit rate and the image quality, it still can be further improved in order to get much lower bit rate for the LASlS interference pattern with the special optical characteristics based on the pushing and sweeping in LASIS imaging principle. In the proposed algorithm FIVQ, the neighborhood of the encoding blocks of the interference pattern image, which are using the mean value rules, will be checked whether they have the same mean value as the current processing block. Experiments show the proposed algorithm FIVQ can get lower bit rate compared to that of the IVQ algorithm for the LASIS interference hyper-spectral sequences. (C) 2014 Elsevier B.V. All rights reserved

关键词： Image compression Vector quantization lbg algorithm Arithmetic coding

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Image vector quantization algorithm via honey bee mating optimization

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EXPERT SYSTEMS WITH APPLICATIONS 2011年第3期38卷 1382-1392页

作者： Horng, Ming-Huwi Jiang, Ting-Wei Natl Pingtung Inst Commerce Dept Comp Sci & Informat Engn Pingtung Taiwan

The vector quantization (VQ) was a powerful technique in the applications of digital image compression. The traditionally widely used method such as the Linde-Buzo-Gray (lbg) algorithm always generated local optimal codebook. Recently, particle swarm optimization (PSO) is adapted to obtain the near-global optimal codebook of vector quantization. An alternative method, called the quantum particle swarm optimization (QPSO) had been developed to improve the results of original PSO algorithm. In this paper, we applied a new swarm algorithm, honey bee mating optimization, to construct the codebook of vector quantization. The results were compared with the other three methods that are lbg, PSO-lbg and QPSO-lbg algorithms. Experimental results showed that the proposed HBMO-lbg algorithm is more reliable and the reconstructed images get higher quality than those generated from the other three methods. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Vector quantization lbg algorithm Particle swarm optimization Quantum particle swarm optimization Honey bee mating optimization

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Efficient greyscale image compression technique based on vector quantization

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OPTO-ELECTRONICS REVIEW 2011年第1期19卷 104-113页

作者： Hu, Y. C. Chuang, J. C. Lo, C. C. Li, C. Y. Providence Univ Dept Comp Sci & Informat Management Taichung 433 Taiwan Providence Univ Dept Comp Sci & Commun Engn Taichung 433 Taiwan Providence Univ Dept Comp Sci & Informat Engn Taichung 433 Taiwan

In this paper, a novel greyscale image coding technique based on vector quantization (VQ) is proposed. In VQ, the reconstructed image quality is restricted by the codebook used in the image encoding/decoding procedures. To provide a better image quality using a fixed-sized codebook, the codebook expansion technique is introduced in the proposed technique. In addition, the block prediction technique and the relatively address technique are employed to cut down the required storage cost of the compressed codes. From the results, it is shown that the proposed technique adaptively provides better image quality at low bit rates than VQ.

关键词： image compression vector quantization codebook design lbg algorithm

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Evolutionary fuzzy particle swarm optimization vector quantization learning scheme in image compression

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EXPERT SYSTEMS WITH APPLICATIONS 2007年第1期32卷 213-222页

作者： Feng, Hsuan-Ming Chen, Ching-Yi Ye, Fun Natl Kinmen Inst Technol Dept Management Informat Kin Ning Vallage 892 Kinmen Taiwan Tamkang Univ Dept Elect Engn Tamsui Taiwan

This article develops an evolutional fuzzy particle swarm optimization (FPSO) learning algorithm to self extract the near optimum codebook of vector quantization (VQ) for carrying on image compression. The fuzzy particle swarm optimization vector quantization (FPSOVQ) learning schemes, combined advantages of the adaptive fuzzy inference method (FIM), the simple VQ concept and the efficient particle swarm optimization (PSO), are considered at the same time to automatically create near optimum codebook to achieve the application of image compression. The FIM is known as a soft decision to measure the relational grade for a given sequence. In our research, the FIM is applied to determine the similar grade between the codebook and the original image patterns. In spite of popular usage of Linde-Buzo-Grey (lbg) algorithm, the powerful evolutional PSO learning algorithm is taken to optimize the fuzzy inference system, which is used to extract appropriate codebooks for compressing several input testing grey-level images. The proposed FPSOVQ learning scheme compared with lbg based VQ learning method is presented to demonstrate its great result in several real image compression examples. (C) 2005 Elsevier Ltd. All rights reserved.

关键词： fuzzy inference analysis particle swarm optimization vector quantization lbg algorithm image compression

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Image compression using modified block truncation coding algorithm

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SIGNAL PROCESSING-IMAGE COMMUNICATION 1998年第1期12卷 1-11页

作者： Chao, CW Hsieh, CH Lu, PC Chung Cheng Inst Technol Dept Elect Engn Tao Yuan 33509 Taiwan I Shou Univ Dept Informat Engn Kaohsiung 84008 Taiwan

This paper presents a modified block truncation coding (ETC) algorithm for image compression. Similar blocks in an image are merged into a cluster and represented with the cluster center. Each cluster center is then encoded with a vision block truncation coding (VBTC) algorithm which uses a small set of predefined binary edge patterns to approximate the bit plane of the cluster center. Experimental results show that the computation efficiency of the proposed algorithm is significantly improved when compared to the original BTC. (C) 1998 Elsevier Science B.V. All rights reserved.

关键词： image compression block truncation coding vector quantization lbg algorithm

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