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An analysis of some common scanning techniques for lossless.image coding

IEEE TRANSACTIONS ON image PROCESSING 2000年第11期9卷 1837-1848页

作者： Memon, N Neuhoff, DL Shende, S Polytech Univ Dept Comp Sci Brooklyn NY 11201 USA Univ Michigan Dept Comp Engn Ann Arbor MI 48109 USA Rutgers State Univ Dept Comp Sci Camden NJ 08102 USA

Though most.image coding techniques use a raster scan to order pixels prior to coding, Hilbert and other scans have been proposed as having better performance due to their superior locality preserving properties. However, a general understanding of the merits of various scans has been lacking. This paper develops an approach for quantitatively analyzing the effect of pixel scan order for context-based, predictive lossless image compression and uses it to compare raster, Hilbert, random and hierarchical scans. Specifically, for a quantized-Gaussian image model and a given scan order, it shows how the encoding rate can be estimated from the frequencies with which various pixel configurations are available as previously scanned contexts, and from the corresponding conditional differential entropies. Formulas are derived for such context frequencies and entropies. Assuming an isotropic image model and contexts consisting of previously scanned adjacent pixels, it is found that the raster scan is better than the Hilbert scan which is often used in compression applications due to its locality preserving properties. The hierarchical scan is better still, though it is based on nonadjacent contexts. The random scan is the worst of the four considered. Extensions and implications of the results to lossy coding are also discussed.

关键词： .image coding coding techniques scanning techniques scan order

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Nonexpansive pyramid for.image coding using a nonlinear filterbank

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IEEE TRANSACTIONS ON image PROCESSING 1998年第2期7卷 246-252页

作者： de Queiroz, RL Florencio, DAF Schafer, RW Xerox Corp Webster NY 14580 USA David Sarnoff Res Ctr Princeton NJ 08544 USA Georgia Inst Technol Sch Elect Engn Atlanta GA 30332 USA

A nonexpansive pyramidal decomposition is proposed for low-complexity.image coding. The image is decomposed through a nonlinear filter bank into low- and highpass signals and the recursion of the filterbank over the lowpass signal generates a pyramid resembling that of the octave wavelet transform. The structure itself guarantees perfect reconstruction and we have chosen nonlinear filters for performance reasons. The transformed samples are grouped into square blocks and used to replace the discrete cosine transform (DCT) in the Joint Photographic Expert Group (JPEG) coder. The proposed coder has some advantages over the DCT-based JPEG: computation is greatly reduced, image edges are better encoded, blocking is eliminated, and it allows lossless coding.

关键词： .image coding Speech Signal lterbank oIEEE

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Set theoretic compression with an application to.image coding

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IEEE TRANSACTIONS ON image PROCESSING 1998年第7期7卷 1051-1056页

作者： Thao, NT Vetterli, M Hong Kong Univ Sci & Technol Dept Elect & Elect Engn Kowloon Hong Kong Hewlett Packard Labs Palo Alto CA 94304 USA EPFL Dept Elect Lausanne Switzerland

We show that the complete information that is available after an image has been encoded is not just an approximate quantized image version, but a whole set of consistent images that contains the original image by necessity. From this starting point, we develop a set of tools to design a new class of encoders for image compression, based on a set decomposition and recombination of image features. As an initial validation, we show the results of an experiment where these tools are used to modify the encoding process of block discrete cosine transform (DCT) coding in order to yield less blocking artifacts.

关键词： .image coding encoders blocking artifacts Scalar quantization

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A fractal vector quantizer for.image coding

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IEEE TRANSACTIONS ON image PROCESSING 1998年第11期7卷 1598-1602页

作者： Kim, CS Kim, RC Lee, SU Seoul Natl Univ Sch Elect Engn Signal Proc Lab Seoul 151742 South Korea Hansung Univ Sch Informat & Comp Engn Seoul South Korea

We investigate the relation between VQ (vector quantization) and fractal.image coding techniques, and propose a novel algorithm for still.image coding, based on fractal vector quantization (FVQ). In FVQ, the source image is approximated coarsely by fixed basis blocks, and the codebook is self-trained from the coarsely approximated image, rather than from an outside training set or the source image itself. Therefore, FVQ is capable of eliminating the redundancy in the codebook without any side information, in addition to exploiting the self-similarity in real images effectively. The computer simulation results demonstrate that the proposed algorithm provides better peak signal-to-noise ratio (PSNR) performance than most other fractal-based coders.

关键词： .image coding vector quantization quantizer real images source image contraction codeword fractal image first stage fractal coders range block conventional fractal

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Hybrid vector quantization for multiresolution.image coding

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IEEE TRANSACTIONS ON image PROCESSING 1997年第5期6卷 753-758页

作者： Rinaldo, R Calvagno, G Dipt. di Elettronica e Inf. Padova Univ

In this correspondence, we propose a coding scheme that exploits the redundancy of the multiresolution representation of images, in that blocks in one subimage are predicted from blocks of the adjacent lower resolution subimage with the same orientation. The pool of blocks used for prediction of a given subband plays the role of a codebook that is built from vectors of coefficients inside the subband decomposition itself. Whenever the prediction procedure does not give satisfactory results with respect to a target quality, the block coefficients are quantized using a geometric vector quantizer for a Laplacian source.

关键词： .image coding vector quantization mean curvature MCD oIEEE inProc

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Progressive decoding method for fractal image compression

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IEE PROCEEDINGS-VISION image AND SIGNAL PROCESSING 2004年第3期151卷 207-213页

作者： He, C Yang, SX Huang, X Chongqing Univ Coll Math & Phys Chongqing 400044 Peoples R China Chongqing Univ Coll Automat Chongqing 400044 Peoples R China

Fractal image compression is an efficient technique for compactly coding images, in which an image is encoded by a contractive transformation whose fixed point is close to the original image, and then is decoded by using an iteration procedure stemmed from the well known Banach fixed-point theorem. A new fixed-point iteration theorem with a control parameter is presented, which provides a novel iteration procedure that progressively approaches the fixed point of a contractive transformation and particularly reverts back to the conventional iteration procedure when the control parameter is set as one. Based on the new iteration procedure, a progressive decoding algorithm is proposed for fractal image compression, which does not need any specific fractal encoder and is useful for low bandwidth transmission. The experimental results demonstrate that the progressive fractal decoding is capable of controlling the decoding iteration procedure by varying the control parameter values and displaying progressively how the original image is obtained from a black image or another image at each step of the increasing iterations.

关键词： .image coding contractive Barnsley

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Comparative analysis of bitplane-based wavelet image coders

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IEE PROCEEDINGS-VISION image AND SIGNAL PROCESSING 2004年第2期151卷 109-118页

作者： Feio, LCRL da Silva, EAB Univ Fed Rio de Janeiro COPPE PEE DELEE BR-21945 Rio De Janeiro Brazil

Wavelet image encoders based on bitplanes give excellent results in the compression of still images. The bitplane concept has recently been generalised to vectors, and wavelet image encoders based on vector bitplanes have been proposed, some achieving slightly better rate x distortion performances than scalar encoders. There remains the open question of whether the use of vector bitplanes has the potential of providing more significant rate x distortion improvements over scalar versions. The authors address this question by analysing in detail the performance of adaptations, for the use of vector bitplanes, of four popular wavelet-based bitplane encoders. From this analysis, they determine where the gains in performance of encoders based on vector bitplanes come from. It is concluded that performance improvements may come by increasing the vector dimension, provided that codebooks with good packing properties are used.

关键词： .image coding SPIHT symbols zerotree wavelet image EZW bitplanes quantisation successive approximation Comparative analysis coefTcients MGE image encoders

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Tracking nonstationary probabilities in adaptive binary arithmetic coding

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IEEE TRANSACTIONS ON image PROCESSING 1998年第12期7卷 1715-1717页

作者： Pennebaker, WB IBM Corp TJ Watson Res Lab Yorktown Heights NY 10598 USA

Adaptive arithmetic coders sometimes exhibit vvnonstationary symbol probabilities when coding digital halftone images with neighborhood-template models. If these nonstationary probabilities vary nonrandomly, the variations can be tracked robustly when each context derived from the coding model is expanded by conditioning on previously coded values for that model context.

关键词： .image coding arithmetic coder repeating statistical behavior pels probability estimate JBIG and JPEG coded pel adaptive template

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