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Conference on Electronic Imaging and Multimedia Systems II

作者： Xu, Y Liu, YW Chen, HX Dai, YS Changchun Inst Posts & Telecommun Dept Sci & Technol Seoul 130012 South Korea

ISBN: (纸本)0819430226

Recently, vector quantization (VQ) has received considerable attention, and has become an effective tool for image compression because of its high compression ratio and simple decoding process. In order to reduce the computational complexity of searching and archiving, tree search can be used in codebook generation which is a major problem of VQ. The Codebook can be generated by a clustering algorithm that selects the most significant vectors of a training set in order to minimize the coding error when all the training set vectors are encoded. Genetic algorithm (GA), a global search method with high robustness, is very effective at finding optimal or near optimal solution to some complex and nonlinear problems. This paper presents a new technique for design a tree-structured vector quantizer using adaptive genetic algorithm. The difference between adaptive GA (AGA) and standard GA is that the probabilities of crossover and mutation of the former are varied depending on fitness values of solutions, thus prove the performance. Experimental results have shown that applying AGA to clustering can accurately locate the clustering centers. In this paper, AGA is used in tree-structured VQ (TSVQ) to generate every node codebook. It is proved theoretically and experimentally that the reconstructed images generated by this method have high visual qualities.

关键词： image compression adaptive genetic algorithm tree-structured vector quantization

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Fine granularity scalable speech coding using embedded tree-structured vector quantization

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SPEECH COMMUNICATION 2012年第1期54卷 23-39页

作者： Djamah, Mouloud O'Shaughnessy, Douglas Univ Quebec INRS EMT Bur 6900 Montreal PQ H5A 1K6 Canada

This paper proposes an efficient codebook design for tree-structured vector quantization (TSVQ) that is embedded in nature. We modify two speech coding standards by replacing their original quantizers for line spectral frequencies (LSF's) and/or Fourier magnitudes quantization with TSVQ-based quantizers. The modified coders are fine-granular bit-rate scalable with gradual change in quality for the synthetic speech. A fast search encoding algorithm using multistage tree-structured vector quantization (MTVQ) is proposed for quantization of LSF's. The proposed method is compared to the multipath sequential tree-assisted search (MSTS) and to the well known multipath sequential search (MSS) or M-L search algorithms. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Embedded quantization Fast search Scalable speech coding tree-structured vector quantization

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Fast codebook search algorithms based on tree-structured vector quantization

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PATTERN RECOGNITION LETTERS 2006年第10期27卷 1077-1086页

作者： Chang, Chin-Chen Li, Yu-Chiang Yeh, Jun-Bin Feng Chia Univ Dept Informat Engn& Comp Sci Taichung 40724 Taiwan Natl Chung Cheng Univ Dept Comp Sci & Informat Engn Chiayi 62102 Taiwan

tree-structured vector quantization (TSVQ) is a highly efficient technique for locating an appropriate codeword for each input vector. The algorithm does not guarantee that the selected codeword is the closest one to the input vector. Consequently, the image quality of TSVQ is worse than that of full-search VQ (FSVQ). Although researchers have proposed multipath TSVQ and DP-TSVQ to enhance the image quality, these methods are still too slow for achieving high image quality. Therefore, this study presents a novel full search equivalent TSVQ (FSE-TSVQ) to obtain efficiently the closest codeword for each input vector. FSE-TSVQ employs the triangle inequality to achieve efficient pruning of impossible codewords. Moreover, this study also develops the enhanced DP-TSVQ (EDP-TSVQ) algorithm, which achieves a better trade-off than DP-TSVQ between encoding time and image quality. EDP-TSVQ is a hybrid technique which adds DP-TSVQ's critical function to FSE-TSVQ. EDP-TSVQ always provides an image quality identical to that of DP-TSVQ, but by searching fewer codebook tree nodes. Simulation results reveal that FSE-TSVQ requires only 21-38% of the running time of FSVQ. For a high image quality application, the performance of EDP-TSVQ is always better than that of DP-TSVQ. Using the example of a codebook tree with 512 codewords, with the threshold of the critical function set to 0.6, simulation results indicate that EDP-TSVQ requires only 37% of the execution time of DP-TSVQ. (c) 2006 Elsevier B.V. All rights reserved.

关键词： codebook search tree-structured vector quantization codebook vector quantization

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Deadzone-constrained pruned tree-structured vector quantization

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IEEE SIGNAL PROCESSING LETTERS 1998年第8期5卷 196-198页

作者： Song, JS Lee, SJ Lee, CW SK Telecom Core Technol Dev Lab Taejon 305348 South Korea Seoul Natl Univ Sch Elect Engn Seoul 151742 South Korea

This letter proposes deadzone-constrained pruned tree-structured vector quantization (DCPTSVQ) which is suitable for transform coding of image or speech. DCPTSVQ applied to transformed signals considerably improves th... 详细信息

关键词： deadzone tree-structured vector quantization

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LOW-COMPLEXITY ENCODING OF SPEECH LSF PARAMETERS USING MULTISTAGE tree-structured vector quantization: APPLICATION TO THE MELP CODER

LOW-COMPLEXITY ENCODING OF SPEECH LSF PARAMETERS USING MULTI...

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22nd IEEE Canadian Conference on Electrical and Computer Engineering

作者： Djamah, M. O'Shaughnessy, D. INRS EMT 800 Montreal PQ H5A 1K6 Canada

ISBN: (纸本)9781424435098

A fast search procedure to reduce the search complexity required to locate the codevectors during the encoding process in multistage tree-structured vector quantization (MTVQ) is proposed. quantization of line spectral frequency (LSF) parameters at different rates is used to provide experimental results, which are compared to the multipath sequential search or M-L search (MSS) and the multipath sequential tree-assisted search (MSTS). The Federal standard MELP coder is modified by replacing the original LSF quantizer with an MTVQ using the proposed fast search procedure, and an evaluation of the produced speech quality is given.

关键词： Fast search LSF speech coding MELP speech coder tree-structured vector quantization

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A UNIFIED APPROACH TO tree-structured AND MULTISTAGE vector quantization FOR NOISY CHANNELS

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IEEE TRANSACTIONS ON INFORMATION THEORY 1993年第3期39卷 835-850页

作者： PHAMDO, N FARVARDIN, N MORIYA, T UNIV MARYLAND INST SYST RES College Pk MD 20742 USA NIPPON TELEGRAPH & TEL PUBL CORP MUSASHINO ELECT COMMUN LAB HUMAN INTERFACE LABS MUSASHINO TOKYO 180 JAPAN

vector quantization (VQ) is a powerful and effective scheme that is widely used in speech and image coding applications. Two basic problems can be associated with VQ: (1) its large encoding complexity, and (2) its sensitivity to channel errors. These two problems have been independently studied in the past. These two problems are examined jointly. Specifically, the performances of two low-complexity VQ's-the tree-structured VQ (TSVQ) and the multistage VQ (MSVQ)-when used over noisy channels are analyzed. An algorithm is developed for the design of channel-matched TSVQ (CM-TSVQ) and channel-matched MSVQ (CM-MSVQ) under the squared-error criterion. Extensive numerical results are given for the memoryless Gaussian source and the Gauss-Markov source with correlation coefficient 0.9. Comparisons with the ordinary TSVQ and MSVQ designed for the noiseless channel show substantial improvements when the channel is very noisy. The CM-MSVQ, which can be regarded as a block-structured combined source-channel coding scheme, is then compared with a block-structured tandem source-channel coding scheme (with the same block length as the CM-MSVQ). For the Gauss-Markov source, the CM-MSVQ outperforms the tandem scheme in all cases that the authors have considered. Furthermore, it is demonstrated that the CM-MSVQ is fairly robust to channel mismatch.

关键词： tree-structured vector quantization MULTISTAGE vector quantization COMBINED SOURCE-CHANNEL CODING

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tree structured vector quantization Based Technique for Speech Compression 1

Tree Structured Vector Quantization Based Technique for Spee...

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1st IEEE International Conference on Data Management, Analytics and Innovation (ICDMAI)

作者： Kanawade, P. R. Gundal, S. S. Amrutvahini Coll Engn Dept Elect Engn Sangamner Maharashtra India

ISBN: (纸本)9781509040834

In this paper, the tree-structured vector quantization (TSVQ) method for proficient speech compression is presented. Efficient utilization of memory is always needed when analog-encoded or digitized data such as image, audio, videos, portable files are need to store and/or convey to digital channels. Compression offers betterments with storage requirements while transmitting the encoded signals with lossy and lossless techniques. Lossy compression is always intended for compression of high volume data with Scalar quantization (SQ) and vector quantization (VQ). The tree based VQ method is used with hieratically organized binary sequences of codeword of data (speech) for compression with reduced and minimized arithmetic calculation requirements. Speech compression has been gained by compressed-codebook coefficients and structured in binary fashion. The quantization noise ratio with signal power is obtained efficiently around less than 1.082 dB. Shared codebook method described in this TSVQ algorithm achieves 3.6 reduced storage requirements of factor 5 to 3.

关键词： Codebook Scalar quantization Signal to quantization Noise Ratio Speech Compression tree-structured vector quantization vector quantization

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AN EFFICIENT tree-structured CODEBOOK DESIGN FOR EMBEDDED vector quantization

AN EFFICIENT TREE-STRUCTURED CODEBOOK DESIGN FOR EMBEDDED VE...

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2010 IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Djamah, Mouloud O'Shaughnessy, Douglas INRS EMT Montreal PQ H5A 1K6 Canada

ISBN: (纸本)9781424442966

This paper proposes an efficient codebook design for tree-structured vector quantization (TSVQ), which is embedded in nature. We modify two speech coding standards by replacing their original quantizers for line spectral frequencies (LSF's) and or Fourier magnitudes quantization with TSVQ-based quantizers. The modified coders are fine-granular bit-rate scalable with gradual change in quality for the synthetic speech.

关键词： Speech coding tree-structured vector quantization embedded quantization scalability

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AN EFFICIENT tree-structured CODEBOOK DESIGN FOR EMBEDDED vector quantization

AN EFFICIENT TREE-STRUCTURED CODEBOOK DESIGN FOR EMBEDDED VE...

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Mouloud DJAMAH Douglas O'Shaughnessy INRS-EMT: 800 de la Gauchetiere Ouest Bureau 6900 Montreal (Quebec) H5A 1K6 CANADA

ISBN: (纸本)9781424442959

This paper proposes an efficient codebook design for tree-structured vector quantization (TSVQ), which is embedded in nature. We modify two speech coding standards by replacing their original quantizers for line spectral frequencies (LSF's) and/or Fourier magnitudes quantization with TSVQ-based quantizers. The modified coders are fine-granular bit-rate scalable with gradual change in quality for the synthetic speech.

关键词： Speech coding tree-structured vector quantization embedded quantization scalability speech coding Scalability quantization vector quantization codebook design quantizer

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Nonproduct Data-Dependent Partitions for Mutual Information Estimation: Strong Consistency and Applications

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2010年第7期58卷 3497-3511页

作者： Silva, Jorge Narayanan, Shrikanth Univ Chile Dept Elect Engn Santiago 4123 Chile Univ So Calif Viterbi Sch Engn Dept Elect Engn Los Angeles CA 90089 USA

A new framework for histogram-based mutual information estimation of probability distributions equipped with density functions in (R(d), B(R(d))) is presented in this work. A general histogram-based estimate is proposed, considering non-product data-dependent partitions, and sufficient conditions are stipulated to guarantee a strongly consistent estimate for mutual information. Two emblematic families of density-free strongly consistent estimates are derived from this result, one based on statistically equivalent blocks (the Gessaman's partition) and the other, on a tree-structured vector quantization scheme.

关键词： Asymptotically sufficient partitions data-dependent partitions histogram-based estimation mutual information tree-structured vector quantization Vapnik-Chervonenkis inequality

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