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differential pulse code modulation predictor design procedure using a genetic algorithm

OPTICAL ENGINEERING 2003年第6期42卷 1649-1655页

作者： Wu, YG Leader Univ Dept Comp Sci & Informat Engn Inst Appl Informat Tainan Taiwan

Digitized images are used widely in current industrial applications;however, digital images cost a huge storage capacity, leading to transmission bandwidth constraints. Therefore, an image compression technique was developed to solve this drawback. differential pulse code modulation (DPCM) is the most widely used method among predictive image coding schemes. It is based on the notation of quantizing a prediction error signal after the prediction operation to reduce the original data complexity. The design of the predictor influences the performance of the whole DPCM. Therefore, the predictor constitutes a central topic in the DPCM system. We make efforts toward the design of a predictor by using a genetic algorithm (GA). By the operations of crossover and mutation, several predictor coefficients are yielded after hundreds of generations. The predictor generated by the GA outperforms the current eight different predictive schemes in Joint Photographic Experts Group lossless (JPEG-LS) still image compression standard. Because the JPEG-LS compression scheme is currently the most widely used lossless compression method, our results contribute to the applications of compression. (C) 2003 Society of Photo-Optical Instrumentation Engineers.

关键词： genetic algorithm differential pulse code modulation image compression signal processing

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Robust Predictive Quantization: Analysis and Design Via Convex Optimization

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IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING 2007年第4期1卷 618-632页

作者： Fletcher, Alyson K. Rangan, Sundeep Goyal, Vivek K. Ramchandran, Kannan Univ Calif Berkeley Berkeley CA 94720 USA Qualcomm Flar Technol Bedminster NJ 07921 USA MIT Cambridge MA 02139 USA

Predictive quantization is a simple and effective method for encoding slowly-varying signals that is widely used in speech and audio coding. It has been known qualitatively that leaving correlation in the encoded samples can lead to improved estimation at the decoder when encoded samples are subject to erasure. However, performance estimation in this case has required Monte Carlo simulation. Provided here is a novel method for efficiently computing the mean-squared error performance of a predictive quantization system with erasures via a convex optimization with linear matrix inequality constraints. The method is based on jump linear system modeling and applies to any autoregressive moving average (ARMA) signal source and any erasure channel described by an aperiodic and irreducible Markov chain. In addition to this quantification for a given encoder filter, a method is presented to design the encoder filter to minimize the reconstruction error. Optimization of the encoder filter is a nonconvex problem, but we are able to parameterize with a single scalar a set of encoder filters that yield low MSE. The design method reduces the prediction gain in the filter, leaving the redundancy in the signal for robustness. This illuminates the basic tradeoff between compression and robustness.

关键词： differential pulse code modulation erasure channels joint source-channel coding linear matrix inequalities

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Uniform scalar quantization based Wyner-Ziv coding of Laplace-Markov source

Uniform scalar quantization based Wyner-Ziv coding of Laplac...

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32nd IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Sheinin, Vadim Jagniohan, Ashish He, Dake IBM T. J. Watson Research United States

ISBN: (纸本)9781424407286

Wyner-Ziv coding has recently emerged as an alternative to conventional DPCM coding for compression of sources with memory, particularly in video compression. This paper studies the operational rate-distortion performance of Wyner-Ziv coding, using uniform scalar quantization followed by perfect Slepian-Wolf coding, for compression of a Laplace-Markov source. The performance gap of this technique relative to DPCM coding is characterized through derived rate-distortion expressions and numerical simulations.

关键词： quantization source coding Wyner-Ziv coding differential pulse code modulation Laplace-Markov source

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Virtually lossless compression of astrophysical images

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EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING 2005年第15期2005卷 2521-2535页

作者： Lastri, C Aiazzi, B Alparone, L Baronti, S CNR Italian Natl Res Council IFAC Inst Appl Phys Nello Carrara I-50127 Florence Italy Univ Florence DET I-50139 Florence Italy

We describe an image compression strategy potentially capable of preserving the scientific quality of astrophysical data, simultaneously allowing a consistent bandwidth reduction to be achieved. Unlike strictly lossless techniques, by which moderate compression ratios are attainable, and conventional lossy techniques, in which the mean square error of the decoded data is globally controlled by users, near-lossless methods are capable of locally constraining the maximum absolute error, based on user's requirements. An advanced lossless/near-lossless differential pulse code modulation (DPCM) scheme, recently introduced by the authors and relying on a causal spatial prediction, is adjusted to the specific characteristics of astrophysical image data (high radiometric resolution, generally low noise, etc.). The background noise is preliminarily estimated to drive the quantization stage for high quality, which is the primary concern in most of astrophysical applications. Extensive experimental results of lossless, near-lossless, and lossy compression of astrophysical images acquired by the Hubble space telescope show the advantages of the proposed method compared to standard techniques like JPEG-LS and JPEG2000. Eventually, the rationale of virtually lossless compression, that is, a noise-adjusted lossles/near-lossless compression, is highlighted and found to be in accordance with concepts well established for the astronomers' community.

关键词： astrophysical images differential pulse code modulation lossless compression near-lossless compression noise estimation statistical context modeling

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Recurrent pi-sigma networks for DPCM image coding

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NEUROCOMPUTING 2003年第1-2期55卷 363-382页

作者： Hussain, AJ Liatsis, P UMIST Dept Elec Engn & Elect Control Syst Ctr Intelligent Syst & Sensing Lab Manchester M60 1QD Lancs England Liverpool John Moores Univ Sch Comp & Math Sci Liverpool L3 3AF Merseyside England

This work proposes a new recurrent polynomial neural network that utilises both the temporal dynamics of the image formation process and the multi-linear interactions between the pixels for 1D/2D predictive image coding. The network consists of a layer of summing units followed by a product unit and incorporates a feedback link from the output to the input layer. It is trained using a small size training set through dynamic backpropagation. Its performance is evaluated on a database of 15 images and compared to the higher-order neural network, the feed-forward pi-sigma neural network, and the standard linear predictor. (C) 2002 Elsevier B.V. All rights reserved.

关键词： recurrent networks higher-order neural networks differential pulse code modulation image compression

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Estimating noise and information of multispectral imagery

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OPTICAL ENGINEERING 2002年第3期41卷 656-668页

作者： Aiazzi, B Alparone, L Barducci, A Baronti, S Pippi, I CNR Natl Res Council Nello Carrara Res Inst Electromagnet Waves IROE I-50127 Florence Italy Univ Florence Dept Elect & Commun I-50139 Florence Italy

We focus on reliably estimating the information conveyed to a user by multispectral image data. The goal is establishing the extent to which an increase in spectral resolution can increase the amount of usable information. As a matter of fact, a trade-off exists between spatial and spectral resolution, due to physical constraints of sensors imaging with a prefixed SNR, After describing some methods developed for automatically estimating the variance of the noise introduced by multispectral imagers, lossless data compression is exploited to measure the useful information content of the multispectral data. In fact, the bit rate achieved by the reversible compression process takes into account both the contribution of the "observation" noise, i.e., information regarded as statistical uncertainty, whose relevance is null to a user, and the intrinsic information of hypothetically noise free multispectral data. An entropic model of the image source is defined and, once the standard deviation of the noise, assumed to be white and Gaussian, has been preliminarily estimated, such a model is inverted to yield an estimate of the information content of the noise-free source from the code rate. Results of both noise and information assessment are reported and discussed on synthetic noisy images and on Landsat thematic mapper (TM) data. (C) 2002 Society of Photo-Optical Instrumentation Engineers.

关键词： bit planes differential pulse code modulation entropy modeling Gaussian distribution interband spectral prediction Landsat thematic mapper linear regression multispectral images

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Compact storage of medical images with patient information

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IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE 2001年第4期5卷 320-323页

作者： Acharya, UR Anand, D Bhat, PS Niranjan, UC Ngee Ann Polytech Dept Elect & Comp Engn Singapore 599489 Singapore New Jersey Inst Technol Dept Elect & Elect Engn Newark NJ 07102 USA Karnataka Reg Engn Coll Dept Elect & Commun Engn Surathkal 574157 India Manipal Inst Technol Dept Biomed Engn Manipal 576119 India

Digital watermarking is a technique of hiding specific identification data for copyright authentication. This technique is adapted here for interleaving patient information with medical images to reduce storage and transmission overheads. The text data are encrypted before interleaving with images to ensure greater security. The graphical signals are compressed and subsequently interleaved with the image. differential pulse-code-modulation and adaptive-delta-modulation techniques are employed for data compression, and encryption and results are tabulated for a specific example.

关键词： adaptive delta modulation differential pulse code modulation interleaving watermarking

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Source-controlled channel decoding using nonbinary turbo codes

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ELECTRONICS LETTERS 2001年第1期37卷 39-40页

作者： Cai, ZH Subramanian, KR Zhang, LR Nanyang Technol Univ Sch EEE Singapore 639798 Singapore

The residual redundancy contained in the source coding output symbols can be used by the channel decoder to provide extra error protection. A joint source/channel coding scheme which employs nonbinary turbo codes over rings to exploit the residual redundancy of source coding output is investigated. Simulation results on codebook-excited linear predictive coded speech and differential pulse code modulation coded image transmissions over noisy channels are presented.

关键词： speech transmission source coding output symbols joint source/channel coding scheme speech coding noisy channels combined source-channel coding turbo codes differential PCM codes image transmission nonbinary turbo codes error protection decoding DPCM coded image transmissions image coding source-controlled channel decoding Image and video coding residual source redundancy differential pulse code modulation redundancy Speech and audio coding codebook-excited linear predictive coded speech error correction

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Shape-VQ-based lossless hybrid ADPCM/DCT coder

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IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING 2000年第4期147卷 313-317页

作者： Wang, J Naghdy, G Univ Wollongong Sch Elect Comp & Telecommun Engn Wollongong NSW 2500 Australia

The discrete cosine transform (DCT) has been shown as an optimum encoder for sharp edges in an image (Andrew and Ogunbona, 1997). A conventional lossless coder employing differential pulse code modulation (DPCM) suffers from significant deficiencies in regions of discontinuity, because the simple model cannot capture the edge information. This problem can be partially solved by partitioning the image into blocks that are supposedly statistically stationary. A hybrid lossless adaptive DPCM (ADPCM)/DCT coder is presented, in which the edge blocks are encoded with DCT, and ADPCM is used for the non-edge blocks. The proposed scheme divides each input image into small blocks and classifies them, using shape vector quantisation (VQ), as either edge or smooth. The edge blocks are further vector quantised, and the side information of the coefficient matrix is saved through the shape-VQ index. Evaluation of the compression performance of the proposed method reveals its superiority over other lossless coders.

关键词： adaptive modulation shape vector quantisation transform coding modulation coding side information nonedge blocks Computer vision and image processing techniques vector quantisation image coding compression performance discrete cosine transforms sharp edges modulation and coding methods image Integral transforms in numerical analysis adaptive differential pulse code modulation coefficient matrix differential pulse code modulation discrete cosine transform Image and video coding shape-VQ-based lossless hybrid ADPCM/DCT coder edge information adaptive DPCM lossless coders Signal processing theory

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Asymptotic performances of DM, DPCM, ADPCM* and Adaptive Quantizer with Variable Range

Asymptotic performances of DM, DPCM, ADPCM* and Adaptive Qua...

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IEEE Information Theory Workshop

作者： Pilipchouk, NI Moscow Inst Phys & Technol Dept Radio Engn Moscow Russia

ISBN: (纸本)0780344081

The main performance such as a mean square error and all average entropy are obtained for the Delta modulation, differential pulse code modulation, Modified Adaptive differential pulse code modulation systems and the Adaptive Quantizer with Variable Range. The input signal is a time-discret first order Gauss-Markov process with the very high correlation of samples. The average transition time of each system is evaluated.

关键词： differential pulse code modulation variable range Mean square error quantizer TRANSIT TIME input signal Self tuning

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