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检索条件"任意字段=Mathematics of Data/Image Coding. Compression, and Encryption"

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mathematics of data/image coding. compression and encryption IV, with Applications

Mathematics of Data/Image Coding, Compression and Encryption...

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2001年

作者： Mark Steven Schmalz

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Erratum: (mathematics of data/image coding. compression, and encryption IV, with Applications (30-31 July 2001))

Proceedings of SPIE - The International Society for Optical ...

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Proceedings of SPIE - The International Society for Optical Engineering 2001年 4475卷 285-285页

作者： Schmalz, Mark S.

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data encryption scheme with extended artithmetic coding

Data encryption scheme with extended artithmetic coding

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4th Conference on mathematics of image and data coding. compression, and encryption

作者： Ishibashi, H Tanaka, K Shinshu Univ Fac Engn Nagano 3808553 Japan

ISBN: (纸本)0819441899

In this work, we extend arithmetic coding.and present a data encryption scheme that achieves data compression and data security at the same time. This scheme is based on a chaotic dynamics, which makes use of the fact that the decoding.process of arithmetic coding.scheme can be considered as the repetition of Bernoulli shift map. data encryption is achieved by controlling the piecewise linear maps by a secret key in three kinds of approach: (i) perturbation method, (ii) switching method, and (iii) source extension method. Experimental results show that the obtained arithmetic codes for a message are randomly distributed on the mapping domain [0,1) by using different keys without seriously deteriorating the compression ratio, and the transition of the orbits in the domain [0,1) is similar to the chaotic dynamics.

关键词： arithmetic coding data encryption data compression chaotic dynamical system pieceivise linear map

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Fast fractal coding.of multispectral remote sensing images

Fast fractal coding of multispectral remote sensing images

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Conference on image compression and encryption Technologies

作者： Lin, NI Univ Sci & Technol China Dept Elect Elect & Informat Sci Hefei 230026 Peoples R China

ISBN: (纸本)0819442798

Fractal image coding.represented the static image data with parameters of dynamic iterating processes and was able to break through the theoretical limitation of entropy coding. It had attracted wide interests of many researchers. In this paper, we applied fractal coding.to multispectral remote sensing image compression and made some improvements to the quad-tree-partition based fractal coding.method according to the properties of multispectral remote sensing images. For the improvements, the same partition scheme was assigned to images in different bands. In addition, the size of the searching space of affine transform was diminished to further improve the compression ratio and also the coding.speed by making use of the spectral correlation. Experimental results showed that the proposed method could improve the performances of the quad-tree-partition based fractal coding.algorithm obviously. Satisfactory results were obtained. Keywords: multispectral remote sensing image, image compression, fast fractal coding. quad-tree partition, sharing quad-tree partition, supervised matching, near-lossless compression, lossless compression, JPEG, DPCM.

关键词： multispectral remote sensing image image compression fast fractal coding quad-tree partition sharing quad-tree partition supervised matching near-lossless compression lossless compression JPEG DPCM

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Lossless data compression in the space applications

Lossless data compression in the space applications

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4th Conference on mathematics of image and data coding. compression, and encryption

作者： Lanza, P Alenia Spazio I-10146 Turin Italy

ISBN: (纸本)0819441899

The first part of the article gives a brief examination of the state of art in terms of methodologies, hardware available and algorithms used in space applications. Particular emphasis is given to the lossless algorithms used and their characterization. In the second part a more detailed analysis, in terms of data entropy, is presented. At the end the preliminary results in the determination of compressibility of the file will be presented.

关键词： entropy data compression estimation of data compression

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An efficient lossless compression scheme for multispectral images

An efficient lossless compression scheme for multispectral i...

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4th Conference on mathematics of image and data coding. compression, and encryption

作者： Benazza-Benyahia, A Hamdi, M Pesquet, JC Ecole Super Commun Tunis Dept Math Appl El Ghazala 2083 Ariana Tunisia

ISBN: (纸本)0819441899

Huge amounts of data are generated thanks to the continuous improvement of remote sensing systems. Archiving this tremendous volume of data is a real challenge which requires lossless compression techniques. Furthermore, progressive coding.constitutes a desirable feature for telebrowsing. To this purpose, a compact and pyramidal representation of the input image has to be generated. Separable multiresolution decompositions have already been proposed for multicomponent images allowing each band to be decomposed separately. It seems however more appropriate to exploit also the spectral correlations. For hyperspectral images, the solution is to apply a 3D decomposition along the spatial and the spectral dimensions. This approach is not appropriate for multispectral images because of the reduced number of spectral bands. In recent works, we have proposed a nonlinear subband decomposition scheme with perfect reconstruction which exploits efficiently both the spatial and the spectral redundancies contained in multispectral images. In this paper, the problem of coding.the coefficients of the resulting subband decomposition is addressed. More precisely, we propose an extension to the vector case of Shapiro's embedded zerotrees of wavelet coefficients (V-EZW) with achieves further saving in the bit stream. Simulations carried out on SPOT images indicate the outperformances of the global compression package we propose.

关键词： multispectral images lossless and progressive coding nonlinear subband decomposition embededd zerotree wavelet coder

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Removal of boundary effects in image compression caused by transforms using non-symmetric local trigonometric bases

Removal of boundary effects in image compression caused by t...

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4th Conference on mathematics of image and data coding. compression, and encryption

作者： Mali, A Palfner, T Müller, E Univ Rostock Inst Commun & Informat Elect D-18119 Rostock Germany

ISBN: (纸本)0819441899

In this paper, we introduce new approaches to remove the boundary artifacts of tile reconstructed images caused by transforms using overlapping non-symmetrical cosine-IV bases in image compression. In tile field of image compression, overlapping cosine-IV bases call reduce the block artifacts that occur in JPEG. These basis functions are longer than the block size and they decay to zero at their boundaries. These cosine-IV bases have, however. one important disadvantage. They are not symmetric. Therefore the symmetric periodic extension cannot be applied to sequences of finite length. Artifacts appear at low bit rates in image compression if only the periodic extension is used. With the aid of the folding operator, we derive the symmetric periodic extension for cosine-IV bases. Weighting functions are introduced. We point out that no artifacts appear at image boundaries if our weighting functions are used. In the second part of our paper, we present a new approach which avoids the extension of the image. There is no overlap at the image boundaries. The efficiency of our proposed methods in image compression is studied. We show, that there are no artifacts at image boundaries in the reconstructed image if our methods are used.

关键词： local trigonometric bases folding/unfolding operator boundary artifacts image compression

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Information-theoretic assessment of imaging systems via data compression

Information-theoretic assessment of imaging systems via data...

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4th Conference on mathematics of image and data coding. compression, and encryption

作者： Aiazzi, B Alparone, L Baronti, S CNR IROE Nello Carrara Res Inst Electromagnet Waves I-50127 Florence Italy

ISBN: (纸本)0819441899

This work focuses on estimating the information conveyed to a user by either multispectral or hyperspectral 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 tradeoff exists between spatial and spectral resolution, due to physical constraints of sensors imaging with a prefixed SNR. Lossless data compression is exploited to measure the useful information content. 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, the relevance of which is null to a user, and the intrinsic information of hypothetically noise-free data. An entropic model of the image source is defined and, once the standard deviation of the noise, assumed to be Gaussian and possibly nonwhite, 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 both of noise and of information assessment are reported and discussed on synthetic noisy images, on Landsat TM data, and on AVIRIS data.

关键词： Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) differential pulse code modulation (DPCM) entropy modeling generalized Gaussian function hyperspectral data interband spectral prediction Landsat Thematic Mapper (TM) linear regression multispectral data noise modeling

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Relative error constrained compression for Synthetic Aperture Radar data

Relative error constrained compression for Synthetic Apertur...

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4th Conference on mathematics of image and data coding. compression, and encryption

作者： Aiazzi, B Alparone, L Baronti, S CNR IROE Nello Carrara Inst Electromagnet Waves I-50127 Florence Italy

ISBN: (纸本)0819441899

Near-lossless compression, i.e., yielding strictly bounded reconstruction error, is extended to preserve the radiometric resolution of data produced by coherent imaging systems, like Synthetic Aperture Radar (SAR). First a causal spatial DPCM based on a fuzzy matching-pursuit (FMP) prediction is adjusted to yield a relative-error bounded compression by applying a logarithmic quantization to the ratio of original to predicted pixel values. Then, a noncausal DPCM is achieved based on the Rational Laplacian Pyramid (RLP), recently introduced by the authors for despeckling. The baseband icon of the RLP is (causally) DPCM encoded, the intermediate layers are uniformly quantized, and the bottom layer is logarithmically quantized. As a consequence, the relative error, i.e., pixel ratio of original to decoded image, can be strictly bounded around unity by the quantization step size of the bottom layer of the RLP. Experimental results reported on true SAR data from NASA/JPL AIRSAR show that virtually lossless images can be achieved with compression ratios larger than three.

关键词： Differential Pulse Code Modulation (DPCM) Rational Laplacian Pyramid (RLP) Synthetic Aperture Radar (SAR) fuzzy logic logarithmic quantization matching pursuits near-lossless compression quantization noise feedback relative error bounded compression speckle

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Spectrum spreading algorithm for efficient embedding of watermarks

Spectrum spreading algorithm for efficient embedding of wate...

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4th Conference on mathematics of image and data coding. compression, and encryption

作者： Yeo, IK Kim, HJ Kangwon Natl Univ Dept Control & Instrumentat Engn Chunchon South Korea

ISBN: (纸本)0819441899

Time-domain and frequency-domain spreading algorithms are presented in this paper. However, detection algorithm does not rely on correlation method, but based on patchwork method. Time-domain algorithm can survive translation and clipping attacks. Frequency-domain algorithm is robust against compression attack. Embedding and detection functions are presented. Simulation results show the effectiveness of the algorithms.

关键词： Digital watermarking Error analysis image processing Detection and tracking algorithms image compression Signal to noise ratio Signal detection Computer simulations image quality Interference (communication)

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