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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： W.D. Leon S. Balkir K. Sayood M.W. Hoffman Department of Electrical Engineering University of Nebraska Lincoln Lincolnshire NE USA

This work presents the design of a computational charge-based circuit to be part of a focal plane compression chip. The image compression scheme pursued is predictive coding. The proposed circuit computes the prediction error at every pixel. It carries out the computations by integrating the photocurrents of the pixels in a small neighborhood. The prediction weights for every pixel can be changed by changing the switching timing of the circuit making possible the use of adaptive prediction algorithms. The circuit is compact and can be integrated at the pixel level.

关键词： Circuits Image coding predictive coding Sensor arrays Transform coding predictive models Pixel Discrete cosine transforms Entropy Signal processing algorithms

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Multiple description motion compensation video coding with leaky prediction

Multiple description motion compensation video coding with l...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Chien-Min Chen Chih-Ming Chen Yung-Chang Chen Department of Electrical Engineering National Tsing Hua University Hsinchu Taiwan

ISBN: (纸本)078038251X

Multiple description (MD) coding has been shown to possess excellent error resilience capability for streaming video over lossy packet networks. Multiple description motion compensation coding (MDMC) also is a MD coding with predictive coding scheme. In such a scheme there are "drift" error propagation, caused by the mismatch between the reference frames used in encoding and decoding. To control error propagation usually lose some predictive efficiency. In this paper, we propose an algorithm based on MD coding with modified multiple description scalar quantization (MDSQ) and leaky predictions to reduce drift without too much lowering of efficiency. Simulation results indicate that the proposed coder with leaky prediction outperforms the normal MDSQ coder even with same prediction scheme. The proposed coder is applicable for error prone wireless networks.

关键词： Motion compensation Video coding Resilience Streaming media predictive coding Encoding Decoding Error correction Quantization predictive models

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Toward optimality in scalable predictive coding

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2001年第7期10卷 965-976页

作者： Rose, K Regunathan, SL Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

A method is proposed for efficient scalability in predictive coding, which overcomes known fundamental shortcomings of the prediction loop at enhancement layers. The compression efficiency of an enhancement-layer is substantially improved by casting the design of its prediction module within an estimation-theoretic framework, and thereby exploiting all information available at that layer fur the prediction of the signal, and encoding of the prediction error. While the most immediately important application is in video compression, the method is derived in a general setting and is applicable to any scalable predictive coder. Thus, the estimation-theoretic approach is first developed for basic DPCM compression and demonstrates the power of the technique in a simple setting that only involves straightforward prediction, scalar quantization, and entropy coding, Results for the scalable compression of first-order Gauss-Markov and Laplace-Markov signals illustrate the performance. A specific estimation algorithm is then developed for standard scalable DCT-based video coding. Simulation results show consistent and substantial performance gains due to optimal estimation at the enhancement-layers.

关键词： .DPCM coder prediction error enhancement-layer predictive coding scalability in predictive prediction module Gauss–Markov Laplace–Markov

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Multiplexed predictive coding of speech

Multiplexed predictive coding of speech

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： S.V. Andersen G. Kubin Department of Speech Music and Hearing KTH Royal Institute of Technology Stockholm Sweden Institute of Communications and Wave Propagation Graz University of Technology Graz Austria

We present a novel method for predictive coding with application to transmission of speech over packet-switched networks. Our method uses multiplexing to distribute a part of the information about a segment of each speech signal in several data packets while keeping the data packet rate and payload for that part of the information unchanged. We investigate three multiplexing schemes: a packet hopping, a Hadamard multiplexing, and an extension of the Hadamard multiplexing that exploits a nonlinear preprocessing and estimation method. We show by means of formal AB-preference tests that multiplexed predictive coding can lead to coders that are more robust to packet losses than scalar quantization and packet loss concealment according to the G.711 standard.

关键词： predictive coding Speech coding Propagation losses Payloads Quantization Robustness Protocols Signal processing Transmitters Degradation

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Performance evaluation of hybrid coding of images using wavelet transform and predictive coding

Performance evaluation of hybrid coding of images using wave...

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International Conference on Computational Intelligence and Multimedia Applications

作者： S.R. Subramanya C. Sabharwal Intelligent Systems Center University of Missouri Rolla Rolla MO USA Department of Computer Science University of Missouri Rolla Rolla MO USA

ISBN: (纸本)0769513123

Image compression techniques are necessary for the storage of huge amounts of digital images using reasonable amounts of space, and for their transmission with limited bandwidth. Several techniques such as predictive coding, transform coding, subband coding, wavelet coding, and vector quantization have been used in image coding. While each technique has some advantages, most practical systems use hybrid techniques which incorporate more than one scheme. They combine the advantages of the individual schemes and enhance the coding effectiveness. This paper proposes and evaluates a hybrid coding scheme for images using wavelet transforms and predictive coding. The performance evaluation is done using a variety of different parameters such as kinds of wavelets, decomposition levels, types of quantizers, predictor coefficients, and quantization levels. The results of evaluation are presented.

关键词： Image coding Wavelet transforms predictive coding Frequency Signal resolution Transform coding Discrete wavelet transforms Vector quantization Signal processing Image storage

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A hybrid lossless compression scheme using region-based predictive coding and integer wavelet transform

A hybrid lossless compression scheme using region-based pred...

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IEEE International Conference on Image Processing

作者： X.Y. Lin L.-K. Shark M.R. Varley B.J. Matuszewski Department of Engineering and Product Design University of Central Lancashire Preston UK

This paper presents a hybrid scheme for lossless compression of the X-ray non-destructive testing (NDT) images of aircraft components. The method combines predictive coding and integer wavelet transform (IWT). Furthermore, with the aid of component CAD models to divide the X-ray images of aircraft components into different regions based on the material structures, the design of the predictors and the choice of the IWT are optimised according to the specific image features contained in each region having the same material structure. Using a real X-ray image of a practical aircraft component, the proposed hybrid scheme is presented and shown to offer a significantly higher compression ratio than other lossless compression schemes.

关键词： Image coding X-ray imaging Aerospace materials Nondestructive testing predictive coding Wavelet transforms Design automation predictive models Aircraft manufacture Design optimization

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Gradient based selective weighting of neighboring pixels for predictive lossless image coding

Gradient based selective weighting of neighboring pixels for...

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International Conference on Information Technology Interfaces

作者： J. Knezovic M. Kovac Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

Natural, continuous tone images have the very important property of high correlation of adjacent pixels. This property is cleverly exploited in lossless image compression where, prior to the statistical modeling and entropy coding step, predictive coding is used as a decorrelation tool. The use of prediction for the current pixel also reduces the cost of the applied statistical model for entropy coding. Linear prediction, where the predicted value is a linear function of previously encoded pixels (causal template), has proven to give very good results as a decorrelation tool in lossless image compression. We concentrate on adaptive linear predictors used in lossless image coding and propose a new linear prediction method.

关键词： Pixel Image coding Entropy coding Costs Decorrelation Context modeling predictive models predictive coding Probability Biomedical imaging

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A drift-free motion-compensated predictive encoding technique for multiple description coding

A drift-free motion-compensated predictive encoding techniqu...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Yen-Chi Lee Y. Altunbasak R.M. Mersereau Center for Signal and Image Processing Georgia Institute of Technology Atlanta GA USA

Multiple description coding (MDC) is a source coding technique that exploits path diversity to increase the robustness of transmitting a compressed signal over error-prone channels. However, the applicant of MDC to video coding is still problematic because a prediction mismatch problem, called drift, may occur at the decoder when one description is lost. In this paper, we propose a drift free motion-compensated predictive coding method for multiple description scalar quantizers. The proposed method maintains two more prediction loops at the encoder side to produce all possible predictions. Then, the two descriptions are generated from these two additional prediction loops in such a way that the drift can be prevented when only one description is received. By receiving both descriptions, the decoder can still combine these two descriptions in the central prediction loop to improve the video quality. Experimental results show that the proposed method can effectively prevent drift and improve the quality of single-description reconstruction by 0.2-0.8 dB as compared to the method in [A. Reibman et al., 1999].

关键词： predictive encoding Decoding Image coding Image reconstruction Source coding Robustness Video coding Signal processing Image processing predictive coding

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Learning and inference in the brain

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NEURAL NETWORKS 2003年第9期16卷 1325-1352页

作者： Friston, KJ UCL Inst Neurol Wellcome Dept Imagin Neurosci London WC1N 3BG England

This article is about how the brain data mines its sensory inputs. There are several architectural principles of functional brain anatomy that have emerged from careful anatomic and physiologic studies over the past century. These principles are considered in the light of representational learning to see if they could have been predicted a priori on the basis of purely theoretical considerations. We first review the organisation of hierarchical sensory cortices, paying special attention to the distinction between forward and backward connections. We then review various approaches to representational learning as special cases of generative models, starting with supervised learning and ending with learning based upon empirical Bayes. The latter predicts many features, such as a hierarchical cortical system, prevalent top-down backward influences and functional asymmetries between forward and backward connections that are seen in the real brain. The key points made in this article are: (i) hierarchical generative models enable the learning of empirical priors and eschew prior assumptions about the causes of sensory input that are inherent in non-hierarchical models. These assumptions are necessary for learning schemes based on information theory and efficient or sparse coding, but are not necessary in a hierarchical context. Critically, the anatomical infrastructure that may implement generative models in the brain is hierarchical. Furthermore, learning based on empirical Bayes can proceed in a biologically plausible way. (ii) The second point is that backward connections are essential if the processes generating inputs cannot be inverted, or the inversion cannot be parameterised. Because these processes involve many-to-one mappings, are non-linear and dynamic in nature, they are generally non-invertible. This enforces an explicit parameterisation of generative models (i.e. backward connections) to afford recognition and suggests that forward architectures, on their ow

关键词： inference predictive coding generative models information theory Bayesian

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Progressive near-lossless coding of medical images 3

Progressive near-lossless coding of medical images

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3rd International Symposium on Image and Signal Processing and Analysis (ISPA)

作者： Krivoulets, A Univ Copenhagen IT DK-1168 Copenhagen Denmark

ISBN: (纸本)953184061X

We propose an algorithm intended for compression of medical images, which allows for embedded coding in Linfinity sense, i.e., progressive near-lossless as well as lossless image compression. The method is based on a lossy plus near-lossless layered compression scheme and embedded quantization of the difference signal. We show that this technique allows for a better image quality and compression performance for large tolerance values than algorithms based on predictive coding. The lossy plus near-lossless scheme also allows for image reconstruction with a minimum mean square error (MSE) criterion, while providing a strict control of the maximum absolute difference error. This property is impossible in predictive coding algorithms.

关键词： Biomedical imaging Decoding Error correction Image coding Image reconstruction Mean square error methods Prediction algorithms predictive coding Signal processing algorithms Streaming media

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