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VECTOR-BASED SIGNAL-PROCESSING AND QUANTIZATION FOR IMAGE AND VIDEO compression

PROCEEDINGS OF THE IEEE 1995年第2期83卷 317-335页

作者： LI, WP ZHANG, YQ GTE LABS INC WALTHAMMA 02254

Image and video compression has become an increasingly important and active area. Many techniques have been developed in this area. Any compression technique can be modeled as a three-stage process. The first stage can be generally called a signal processing stage where an image or video signal is converted into a different domain. Usually, there is no or little loss of information in this stage. The second stage is quantization where loss of information occurs. The third stage is lossless coding that generates the compressed bit stream. The purpose of the signal processing stage is to convert an image or video signal into such a form that quantization can achieve better performance than without the signal processing stage. Because the quantization stage is the place where most of compression is achieved and loss of information occurs, it is naturally the central stage of any compression technique. Since scalar quantization or vector quantization may be used in the second stage, the operation in the first stage should be scalar-based or vector-based respectively in order to match the second stage so that the compression performance can be optimized. In this paper, we summarize the most recent research results on vector-based signal processing and quantization techniques that have shown high compression performance.

关键词： Video signal processing Quantization Video compression Image coding Image converters Signal processing Signal processing algorithms Very large scale integration compression algorithms Bit rate

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FILTERING RANDOM NOISE FROM DETERMINISTIC SIGNALS VIA DATA-compression

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 1995年第11期43卷 2595-2605页

作者： NATARAJAN, BK Hewlett Packard Laboratories Palo Alto CA USA

We present a novel technique for the design of filters for random noise, leading to a class of filters called Occam filters. The essence of the technique is that when a lossy data compression algorithm is applied to a noisy signal with the allowed loss set equal to the noise strength, the loss and the noise tend to cancel rather than add. We give two illustrative applications of the technique to univariate signals. We also prove asymptotic convergence bounds on the effectiveness of Occam filters.

关键词： Filtering Data compression Noise cancellation Wiener filter Nonlinear filters compression algorithms Additive noise Convergence Power measurement Noise measurement

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SPECTRAL AND SPATIAL DECORRELATION OF LANDSAT-TM DATA FOR LOSSLESS compression

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1995年第5期33卷 1277-1285页

作者： WANG, JF ZHANG, KH TANG, SW UNIV WESTERN ONTARIO DEPT COMP SCILONDONON N6A 5B7CANADA BEIJING COMP INST DEPT COMP SCIBEIJINGPEOPLES R CHINA

This paper presents some new techniques of spectral and spatial decorrelation in lossless data compression of remotely sensed imagery. These techniques provide methods to efficiently compute the optimal band combination and band ordering based on the statistical properties of Landsat-TM data. Experiments on several Landsat-TM images show that using both the spectral and the spatial nature of the remotely sensed data results in significant improvement over spatial decorrelation alone. These techniques result in higher compression ratios and are computationally inexpensive.

关键词： Decorrelation Satellites Remote sensing Image coding Data compression Computer science Reflectivity Image reconstruction compression algorithms Councils

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APPLYING WAVELET TRANSFORMS WITH ARITHMETIC CODING TO RADIOLOGICAL IMAGE compression

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IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE 1995年第5期14卷 587-593页

作者： SAIPETCH, P HO, BKT PANWAR, R MA, M WEI, J Department of Radiological Sciences University of California Los Angeles USA

Radiological archives need the images to be compressed at a moderate compression ratio between 10:1 to 20:1 while retaining good diagnostic quality. We have developed a compression algorithm based on discrete wavelet transforms (DWTs) and arithmetic coding (AC) that satisfies those requirements. This new method is superior to the previously developed full frame discrete cosine transform (FFDCT) method, as well as the industrial standard developed by the joint photographic expert group (JPEG). Since DWT is localized in both spatial and scale domains, the error due to quantization of coefficients does not propagate throughout the reconstructed picture as in FFDCT. Because it is a global transformation, it does not suffer the limitation of block transform methods such as JPEG. The severity of the error as measured by the normalized mean square error (NMSE) and maximum difference technique increases very slowly with compression ratio compared to the FFDCT. Normalized nearest neighbor difference (NNND), which is a measure of blockiness, stays approximately constant, while JPEG NNND increases rapidly with compression ratio. Furthermore, DWT has an efficient finite response filter FlR implementation that can be put in parallel hardware. DWT also offers total flexibility in the image format; the size of the image does not have to be a power of two as in the case of FFDCT.< >

关键词： Wavelet transforms Arithmetic Discrete wavelet transforms Image coding Transform coding compression algorithms Discrete cosine transforms Standards development Quantization Image reconstruction

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DATA-compression AND PERCEIVED QUALITY

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IEEE SIGNAL PROCESSING MAGAZINE 1995年第5期12卷 58-59页

作者： SMITH, JL Simulation and Signature Department at the Guided Weapons Evaluation Facility Vitro Technical Services FL USA

Discusses image compression and the block compression algorithm (BCA). The power spectrum, Bode diagram, or modulation transfer function (MTF) for the transmitted, reconstructed signal are the usual measures of system resolution. Any one of these resolution measures is often nearly identical for the ordinary signal and that for which the BCA is used. Yet, observers of that same transmitted signals perceive a much more profound difference than indicated by the resolution measure. At high compression, they say it is choppy and disturbing for the dynamic features. The author discusses how one can describe a measure of the effect of the BCA on the observation.< >

关键词： Data compression Human factors Signal resolution Computer vision Power measurement Noise level Gaussian noise Image coding Microwave communication compression algorithms

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MANIPULATION AND COMPOSITING OF MC-DCT COMPRESSED VIDEO

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 1995年第1期13卷 1-11页

作者： CHANG, SF MESSERSCHMITT, DG COLUMBIA UNIV CTR TELECOMMUN RESNEW YORKNY 10027 UNIV CALIF BERKELEY DEPT EECSBERKELEYCA 94720

Many advanced video applications require manipulations of compressed video signals. Popular video manipulation functions include overlap (opaque or semitransparent), translation, scaling, linear filtering, rotation, and pixel multiplication. In this paper, we propose algorithms to manipulate compressed video in the compressed domain. Specifically, we focus on compression algorithms using the discrete cosine transform (DCT) with or without motion compensation (MC). compression systems of such kind include JPEG, motion JPEG, MPEG, and H.261. We derive a complete set of algorithms for all aforementioned manipulation functions in the transform domain, in which video signals are represented by quantized transform coefficients. Due to a much lower data rate and the elimination of decompression/compression conversion, the transform-domain approach has great potential in reducing the computational complexity. The actual computational speedup depends on the specific manipulation functions and the compression characteristics of the input video, such as the compression rate and the nonzero motion vector percentage. The proposed techniques can be applied to general orthogonal transforms, such as discrete trigonometric transform. For compression systems incorporating MC (such as MPEG), we propose a new decoding algorithm to reconstruct the video in the transform domain and then perform the desired manipulations in the transform domain. The same technique can be applied to efficient video transcoding (e.g., from MPEG to JPEG) with minimal decoding.

关键词： Video compression Transform coding Discrete transforms Discrete cosine transforms Decoding Maximum likelihood detection compression algorithms Motion compensation Computational complexity Transcoding

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PORTABLE VIDEO-ON-DEMAND IN WIRELESS COMMUNICATION

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PROCEEDINGS OF THE IEEE 1995年第4期83卷 659-680页

作者： MENG, TH GORDON, BM TSERN, EK HUNG, AC Department of Electrical Engineering University of Stanford Stanford CA USA

Our present ability to work with video has been confined to a wired environment, requiring both the video encoder and decoder to be physically connected to a power supply and a wired communication link. This paper describes An integrated approach to the design of a portable video-on-demand system capable of delivering high-quality image and video data in a wireless communication environment. The discussion will focus on both the algorithm and circuit design techniques developed for implementing a low-power video compression/decompression system at power levels that are two orders of magnitude below existing solutions. This low-power video compression system not only provides a compression efficiency similar to industry standards, but also maintains a high degree of error tolerance to guard against transmission errors often encountered in wireless communication The required power reduction can best be attained through reformulating compression algorithms for energy conservation. We developed an intra-frame compression algorithm that requires minimal computation energy in its hardware implementations. Examples of algorithmic trade-offs are the development of a vector quantization scheme that allows on-chip computation to eliminate off-chip memory accesses, the use fo channel-optimized delta representations to avoid the error control hardware that would otherwise be necessary and the coding of internal data representations to further reduce the energy consumed in data exchanges, The architectural and circuit design techniques used include the selection of a filter bank structure that minimizes the energy consumed in the datapath, the data shuffle strategy that results in reduced internal memory size, and the design of digital and analog circuits optimized for low supply voltages, Our hardware prototype is a video decoding chip set for decompressing full-motion video transmitted through a wireless link at less than 10 mW, which is incorporated into a hand-held portable

关键词： Wireless communication Video compression compression algorithms Decoding Power supplies Circuit synthesis Communication industry Communication standards Energy conservation Hardware

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A VLSI ARCHITECTURE FOR HIERARCHICAL MOTION ESTIMATION

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IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 1995年第2期41卷 248-257页

作者： COSTA, A DEGLORIA, A FARABOSCHI, P PASSAGGIO, F Department of BioPhysics and Electrical Engineering DIBE University of Genova Genoa Italy

Motion estimation is the critical path in compression algorithms, and several dedicated hardware solutions have been proposed for its acceleration. In this paper we present an innovative VLSI architecture for Motion Estimation that combines a low implementation cost with real-time performance for videoconferencing and DTV standards. To minimize computational load and architecture requirements, we adopt a three-step hierarchical search algorithm, that provides a quality comparable with more expensive full-search techniques. The proposed solution focuses on architectural efficiency by employing a minimum set of functional units (three simple processing units, one minimum unit, and four programmable delay lines), still supporting realtime performance for videoconferencing standards. In addition we show how to combine parallel Motion Estimation Units for backward-forward prediction (MPEG) and for higher throughput standards (DTV).

关键词： Videoconferencing compression algorithms search technique Digital television acceleration SEARCHING ALGORITHM DELAY LINES motion estimation

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EFFECT OF WAVELET BASES ON COMPRESSING DIGITAL MAMMOGRAMS

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IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE 1995年第5期14卷 570-577页

作者： YANG, ZS KALLERGI, M DEVORE, RA LUCIER, BJ QIAN, W CLARK, RA CLARK, LP Department of Mathematics University of South Carolina USA Department of Mathematics Purdue University USA Department of Radiology University of South Florida USA

The purposes of this paper are four-fold: (a) develop a variety of wavelet methods, including standard, hyperbolic, and adaptive wavelet bases, for the compression of high-resolution digital mammograms, (b) apply different levels of compression to the images and determine the dependence of the information loss on the compression ratio, (c) determine qualitatively the types of artifacts and errors introduced to the compressed reconstructed images by the various wavelets and make a relative comparison, and (d) discriminate among the various wavelet bases and select those worthy of further analysis and study.< >

关键词： Image coding Image reconstruction Wavelet analysis Transform coding Biomedical imaging compression algorithms Dynamic range Memory Large screen displays Biomedical engineering

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Segmentation-assisted compression of multimedia documents

Segmentation-assisted compression of multimedia documents

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Asilomar Conference on Signals, Systems & Computers

作者： N. Chaddha Computer Systems Laboratory University of Stanford Stanford CA USA

Block-based compression algorithms have found widespread use in image and video compression standards. algorithms such as JPEG, however, while very effective in compressing continuous tone images, do not perform well in compressing multimedia documents which contain text and graphics. With a growing number of applications using images with a high content of both continuous tone data and text, e.g. color facsimile data and educational videos, requires the need for a good compression algorithm. In this paper we present a modified JPEG algorithm for compressing such mixed-mode images which occur in multimedia documents. The algorithm is based on the classification of a block as a kind of text or an image block depending on its DCT coefficients. There can be anywhere from 2 to 256 classes. With such a classification, the same compression algorithm can be applied except that different quantization matrices are used for the different type of blocks. The compression algorithm also uses different entropy codes for the different type of blocks. Simulation results show that the modified JPEG algorithm achieves upto 3 dB gain in PSNR compared to JPEG on multimedia documents.

关键词： Image coding compression algorithms Transform coding Video compression Image segmentation Graphics Facsimile Discrete cosine transforms Quantization Entropy

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