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

共 163 条记录，以下是91-100 订阅

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Proceedings of SPIE: mathematics of data/image coding. compression, and encryption V, with Application

Proceedings of SPIE: Mathematics of Data/Image Coding, Compr...

引用

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

This Volume 4793 of the conference proceedings contains 34 papers. Topics discussed include mathematics of data/image coding. compression, and encryption and security, remote sensing and communication and compressive ... 详细信息

关键词： image coding

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Message encryption with image processing

Message encryption with image processing

引用

IEEE International Conference on Multi Topic

作者： S.M. Ashar T.M. Shah R. Khalid Department of Computer Science International Islamic University Islamabad Pakistan Department of Computer Science Khadim Ali Shah Bukhari Institute of Technology Karachi Pakistan

The paper proposes a new steganographic model for secret data communication. A stack of four modules is used. The "compression module" gives the benefit of entropy coding. The "cryptographic module" provides confidentiality in the communication. To preserve integrity of data, the "hash module" is used with a shared secret key. A technique is proposed in which it is not required that the receiver should know the secret key before reception of the message. For the "steganographic module", an image steganographic method is proposed that is derived from the method of Yeuan-Kuen Lee and Ling-Hwei Chen (see IEEE Proc. Vision, image and Sig. Process., 2000). As compared to that method, we make little use of the smooth regions of the cover image that provides better image fidelity and perceptual transparency. The proposed method can also hide data in 24 bit true color images. Furthermore, we spread the data on the whole image instead of using part of the image. This steganographic method is used to hide the encrypted communication. Experimental results show the effectiveness and efficiency of the proposed model

关键词： image processing Steganography Elliptic curve cryptography Public key cryptography Computer science image coding Color Information security data communication Internet

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Entropy-constrained predictive compression of SAR raw data

Entropy-constrained predictive compression of SAR raw data

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Conference on mathematics of data/image coding. compression and encryption V, with Applications

作者： Magli, E Olmo, G Politecn Torino Dipartimento Elettron I-10129 Turin Italy

ISBN: (纸本)0819445606

In this paper we propose to employ entropy-constrained predictive coding.for lossy compression of SAR raw data. We exploit the known result that a blockwise normalized SAR raw signal is a Gaussian stationary process in order to design an optimal decorrelator for this signal. The proposed predictive coding.algorithm performs entropy-constrained quantization of the prediction error, followed by entropy coding.the algorithm exhibits a number of advantages, and notably a very high performance gain, with respect to other techniques such as FBAQ or methods based on transform coding. Simulation results on real-world SIR-C/X-SAR as well as simulated raw and image data show that the proposed algorithm significantly outperforms FBAQ as to SNR, at a computational cost compatible with modem SAR systems.

关键词： SAR raw data compression DPCM entropy coding entropy-constrained quantization

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A comparison of lossy compression methods on still and hyperspectral images

A comparison of lossy compression methods on still and hyper...

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Conference on mathematics of data/image coding. compression and encryption V, with Applications

作者： Serra-Sagristà, J Borrell, J Univ Autonoma Barcelona Dept Comp Sci Escola Tecn Super Engn E-08193 Cerdanyola Del Valles Barcelona Spain

ISBN: (纸本)0819445606

The statistical dependency across levels (or scales) in the wavelet transform of natural images can be effectively exploited to design state-of-the-art image coders. This paper presents a comparative evaluation of three such algorithms, although only one of these algorithms is detailed to a larger extend. The first method explicitly models the conditional statistics of the wavelet coefficients for bit-plane encoding. The second method performs an implicit sorting of the coefficients by sending zerotree symbols. Both methods produce an embedded code, i.e. the optimal image at any rate can be identified with the truncated bitstream of the highest possible rate, but the second algorithm does not depend as much as the first on the use of arithmetic coding. The third method is based on lattice vector quantization: statistical dependency within the wavelet transform is taken into account by conditioning the encoding.of the vector norm on the value of a predictor. All three algorithms yield approximately comparable experimental results for different corpuses of images. This supports our view that the essence of high performance image compression is a careful modeling of the conditional image statistics.

关键词： image coding hyperspectral images lattice vector quantization wavelet transform

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A best wavelet packet basis for joint image deblurring-denoising and compression

A best wavelet packet basis for joint image deblurring-denoi...

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Conference on mathematics of data/image coding. compression and encryption V, with Applications

作者： Dhérété, P Durand, S Froment, J Rougé, B THALES Informat Syst F-31037 Toulouse France

ISBN: (纸本)0819445606

We propose a unique mathematical framework to deblur, denoise and compress natural images. images are decomposed in a wavelet packet basis adapted both to the deblurring filter and to the denoising process. Effective denoising is performed by thresholding small wavelet packet coefficients while deblurring is obtained by multiplying the coefficients with a deconvolution kernel. This representation is compressed by quantizing the remaining coefficients and by coding.the values using a context-based entropy coder. We present examples of such treatments on a satellite image chain. The results show a significant improvement compared to separate treatments with up-to-date compression approach.

关键词： image enhancement

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Vector-lifting schemes based on sorting techniques for lossless compression of multispectral images

Vector-lifting schemes based on sorting techniques for lossl...

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Conference on mathematics of data/image coding. compression and encryption V, with Applications

作者： Benazza-Benyahia, A Pesquet, JC Ecole Super Commun SUPCOM El Ghazala 2083 Ariana Tunisia

ISBN: (纸本)0819445606

In this paper, we introduce vector-lifting schemes which allow to generate very compact multiresolution representations, suitable for lossless and progressive coding.of multispectral images. These new decomposition schemes exploit simultaneously the spatial and the spectral redundancies contained in multispectral images. When the spectral bands have different dynamic ranges, we improve dramatically the performances of the proposed schemes by a reversible histogram modification based on sorting permutations. Simulation tests carried out on real images allow to evaluate the performances of this new compression method. They indicate that the achieved compression ratios are higher than those obtained with currently used lossless coders.

关键词： multicomponent images lossless and progressive coding nonlinear subband decomposition histogram modification

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Near-lossless image compression by adaptive prediction: new developments and comparison of algorithms

Near-lossless image compression by adaptive prediction: new ...

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Conference on mathematics of data/image coding. compression and encryption V, with Applications

作者： Aiazzi, B Alparone, L Baronti, S CNR IFAC Inst Appl Phys N Carrara I-50127 Florence Italy

ISBN: (纸本)0819445606

This paper describes state-of-the-art approaches to near-lossless image compression by adaptive causal DPCM and presents two advanced schemes based on crisp and fuzzy switching of predictors, respectively. The former relies on a linear-regression prediction in which a different predictor is employed for each image block. Such block-representative predictors are calculated from the original data set through an iterative relaxation-labeling procedure. coding.time are affordable thanks to fast convergence of training. Decoding.is always performed in real time. The latter is still based on adaptive MMSE prediction in which a different predictor at each pixel position is achieved by blending a number of prototype predictors through adaptive weights calculated from the past decoded samples. Quantization error feedback loops are introduced into the basic lossless encoders to enable user-defined upper-bounded reconstruction errors. Both schemes exploit context modeling of prediction errors followed by arithmetic coding.to enhance entropy coding.performances. A thorough performance comparison on a wide test image set show the superiority of the proposed schemes over both up-to-date encoders in the literature and new/upcoming standards.

关键词： adaptive DPCM classified DPCM differential pulse code modulation (DPCM) entropy coding fuzzy logic image compression near-lossless compression adaptive prediction relaxation labeling statistical context modeling

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Dynamic sub-wavelength encryption

Dynamic sub-wavelength encryption

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Conference on mathematics of data/image coding. compression and encryption V, with Applications

作者： Eckhouse, V Zalevsky, Z Mendlovic, D Tel Aviv Univ Fac Engn Dept Phys Elect IL-69978 Tel Aviv Israel

ISBN: (纸本)0819445606

The suggested device includes a spatial light modulator (SLM) allowing varying the polarization state of an input illumination source. Attached to the SLM a sub wavelength grating is placed per each pixel of the device. This grating is used to encode the input information. The decoding.is done by another sub wavelength grating. When the two gratings are attached a variation of the energetic efficiency between the two polarization states occurs. The polarization ratio encrypts the spatial information strewn. The sub wavelength grating are hard to copy and thus high encryption capability is obtained.

关键词： super resolution sub wavelength encryption

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Integer optimization methods for non-MSE data compression for emitter location

Integer optimization methods for non-MSE data compression fo...

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

作者： Fowler, Mark L. Chen, Mo Dept. of Elec. and Comp. Eng. State Univ. of New York Binghamton Binghamton NY 13902 United States

The location of an emitter is estimated by intercepting its signal and sharing the data among several platforms to measure the time-difference-of- arrival (TDOA) and the frequency-difference-of-arrival (FDOA). Doing this in a timely fashion requires effective data compression. A common compression approach is to use a rate-distortion criterion where distortion is taken to be the mean-square error (MSE) between the original and compressed versions of the signal. However, in this paper we show that this MSE-only approach is inappropriate for TDOA/FDOA estimation and then define a more appropriate, non-MSE distortion measure. This measure is based on the fact that in addition to the dependence on MSE. the TDOA accuracy also depends inversely on the signal's RMS (or Gabor) bandwidth and the FDOA accuracy also depends inversely on the signal's RMS (or Gabor) duration. We develop specific forms of this new non-MSE distortion measure and apply it to the case of using the DFT for compression. The form of this new measure must be optimized under the constraint of a specified budget on the total number of bits available for coding. We show that this optimization requires a selection of DFT cells to retain that must be jointly chosen with an appropriate allocation of bits to the selected DFT cells. This joint selection/allocation is a challenging integer optimization problem that still has not been solved. However, we consider three possible sub-optimal approaches and compare their performance.

关键词： data compression

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Lossy compression of multispectral remote-sensing images through multiresolution data fusion techniques

Lossy compression of multispectral remote-sensing images thr...

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Conference on mathematics of data/image coding. compression and encryption V, with Applications

作者： Aiazzi, B Alparone, L Baronti, S Selva, M CNR IFAC Inst Appl Phys N Carrara I-50127 Florence Italy

ISBN: (纸本)0819445606

This work reports about a specific application concerning lossy compression of multispectral (MS) and panchromatic (P) images collected by spaceborne platforms. Generally, the former is a set of narrow-band spectral images, while the latter is a single broad-band observation imaged in the visible and near-infrared wavelengths. Since high resolution spectral observations having high SNR are difficult to obtain, and especially to transmit, the P image, having resolution typically four times that of MS, but slightly lower SNR, is added to the MS data and used with the main purpose of expediting both visual and automatic identification tasks, possibly through an integration (merge) with the lower resolution MS data. Whenever MS data at the same resolution of the P data and with adequate SNR were hypotetically available on board, the bottleneck of downlink to receiving stations would impose severe limitations in the bit rate, so that a lossy compression would be mandatory. The consequence of the loss of information is a distortion, both radiometric and especially spectral, which may be easily quantified. Experimental results were carried out on simulated SPOT 5 data, constituted by three 10m MS bands (XS) and one 2.5m P band, all 8 b/pel, of a highly detailed urban area. The main result is that, for cumulative bit rates larger than 4.2 b/pel (at a 2.5m scale), lossless compression of the three 10m XS bands and near-lossless compression of the 2.5m P band, followed by XS + P fusion of the data decoded at the receiving station, is preferable, in terms of radiometric and especially of spectral distortion, to lossy compression of the three 2.5m XS bands, even if data with such a resolution were hypotetically available on board.

关键词： adaptive prediction data fusion differential pulse code modulation (DPCM) Laplacian pyramids multiresolution analysis multispectral images near-lossless compression radiometric distortion remote sensing spectral distortion

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