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

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Proceedings of SPIE - mathematics of data/image Pattern Recognition, compression, and encryption with Applications IX

Proceedings of SPIE - Mathematics of Data/Image Pattern Reco...

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mathematics of data/image Pattern Recognition, compression, and encryption with Applications IX

ISBN: (纸本)0819463949

The proceedings contain 23 papers. The topics discussed include: biorthogonal wavelets of maximum coding.through pseudoframes for subspaces;a skinning prediction scheme for dynamic 3D mesh compression;multi-modal multi-fractal boundary encoding.in object-based image compression;perspectives on data compression methods for network-level management of multi-sensor systems;exploiting data compression methods for network-level management of multi-sensor systems;a model utilizing artificial neural network for perceptual image;use of adaptive models in watermark identification;data payload optimality: a key issue for for video watermarking applications;quantization index modulation-based watermarking using holography;the optimum estimation of statistical signals based on systematic expression of many types of sample arrays in multidimensional space;and segmentation of motion textures using mixed-state Markov random fields.

关键词： Pattern recognition

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A model utilizing artificial neural network for perceptual image quality assessment in image compression algorithms

A model utilizing artificial neural network for perceptual i...

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mathematics of data/image Pattern Recognition, compression, and encryption with Applications IX

作者： Fliegel, Karel Czech Technical University in Prague Faculty of Electrical Engineering Department of Radioelectronics Technická 2 166 27 Prague 6 Czech Republic

ISBN: (纸本)0819463949

The demand of an accurate objective image quality assessment tool is important in modern multimedia systems. image coding.algorithms introduce highly structured coding.artifacts and distortions. In this paper, we present a novel approach to predict the perceived image quality. Properties of the Human Visual System (HVS) were exploited to select a set of suitable metrics. These metrics are extracted while comparing the reference and distorted image. Mutual Information (MI) and Principal Component Analysis (PCA) were used to obtain an optimal set of objective features that best describe the perceived image quality in respect to subjective scores from human observers. The impairment feature vector is forwarded to the Artificial Neural Network (ANN) where the features are combined and the predicted quality score is computed. Parameters of the ANN are adjusted using Mean Opinion Scores (MOS) obtained from the group of assessors. It is shown that the proposed image quality assessment model can achieve high correlation with the subjective image quality ratings. Possible incorporation of the model into a perceptual image-coding.algorithm is proposed. Such a system is capable to ensure that only visually important information is encoded and consequently that the required communication bandwidth is minimized.

关键词： Neural networks

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Multi-modal, multi-fractal boundary encoding.in object-based image compression

Multi-modal, multi-fractal boundary encoding in object-based...

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Conference on mathematics of data/image Pattern Recognition, compression and encryption with Application IX

作者： Schmalz, Mark S. Univ Florida Ctr Comp Vis & Visualizat Gainesville FL 32611 USA

ISBN: (纸本)0819463949

The compact representation of region boundary contours is key to efficient representation and compression of digital images using object-based compression (OBC). In OBC, regions are coded in terms of their texture, color, and shape. Given the appropriate representation scheme, high compression ratios (e.g., 500:1 <= CR <= 2,500:1) have been reported for selected images. Because a region boundary is often represented with more parameters than the region contents, it is crucial to maximize the boundary compression ratio by reducing these parameters. Researchers have elsewhere shown that cherished boundary encoding.techniques such as chain coding. simplicial complexes, or quadtrees, to name but a few, are inadequate to support OBC within the aforementioned CR range. Several existing compression standards such as MPEG [1] support efficient boundary representation, but do not necessarily support OBC at CR >= 500:1 [2]. Siddiqui et al. [3] exploited concepts from fractal geometry to encode and compress region boundaries based on fractal dimension, reporting CR = 286.6:1 in one test. However, Siddiqui's algorithm is costly and appears to contain ambiguities. In this paper, we first discuss fractal dimension and OBC compression ratio, then enhance Siddiqui's algorithm, achieving significantly higher CR for a wide variety of boundary types. In particular, our algorithm smoothes a region boundary B, then extracts its inflection or control points P, which are compactly represented. The fractal dimension D is computed locally for the detrended B. By appropriate subsampling, one efficiently segments disjoint clusters of D values subject to a preselected tolerance, thereby partitioning B into a multifractal. This is accomplished using four possible compression modes. In contrast, previous researchers have characterized boundary variance with one fractal dimension, thereby producing a monofractal. At its most complex, the compressed representation contains P, a spatial marker, and

关键词： object-based image compression representation fractal dimension

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Proceedings of SPIE mathematics of data/image coding. compression, and encryption VIII, with Applications

Proceedings of SPIE Mathematics of Data/Image Coding, Compre...

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

The proceedings contain 21 papers. The topics discussed include: a cryptanalysis procedure of the data encryption standard;an adaptive watermarking scheme in the DCT domain;robust video watermarking using additional watermarking techniques;computational complexity of object-based image compression;error measures for object-based image compression;exploiting the distributed source coding.paradigm for low-complexity compression of hyperspectral images;fast feature extraction in hyperspectral imagery via lifting wavelet transforms;deformable block motion compensation scheme for aerial video surveillance coding.minimax eigenvector decomposition for data hiding;and selective weighing on wavelet coefficients for blind image watermarking system.

关键词： Imaging systems

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On encryption-compression tradeoff of pre/post-filtered images

On encryption-compression tradeoff of pre/post-filtered imag...

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

作者： Gurijala, Aparna Khayam, Syed A. Radha, Hayder Deller Jr., J.R. Department of Electrical and Computer Engineering 2120 Engineering Building Michigan State University East Lansing MI 48824

Advances in network communications have necessitated secure local-storage and transmission of multimedia content. In particular, military networks need to securely store sensitive imagery which at a later stage may be transmitted over bandwidth-constrained wireless networks. This work investigates compression efficiency of JPEG and JPEG 2000 standards for encrypted images. An encryption technique proposed by Kuo et al. in [4] is employed. The technique scrambles the phase spectrum of an image by addition of the phase of an all-pass pre-filter. The post-filter inverts the encryption process, provided the correct pseudo-random filter coefficients are available at the receiver. Additional benefits of pre/post-filter encryption include the prevention of blocking effects and better robustness to channel noise [4]. Since both JPEG and JPEG 2000 exploit spatial and perceptual redundancies for compression, pre/post-filtered (encrypted) images are susceptible to compression inefficiencies. The PSNR difference between the unencrypted and pre/post-filtered images after decompression is determined for various compression rates. compression efficiency decreases with an increase in compression rate. For JPEG and JPEG 2000 compression rates between 0.5 to 2.5 bpp, the difference in PSNR is negligible. Partial encryption is proposed wherein a subset of image phase coefficients are scrambled. Due to the phase sensitivity of images, even partial scrambling of the phase information results in unintelligible data. The effect of compression on partially encrypted images is observed for various bit-rates. When 25% of image phase coefficients are scrambled, the JPEG and JPEG 2000 compression performance of encrypted images is almost similar to that of unencrypted images for compression rates in the 0.5 to 3.5 bpp range.

关键词： image compression

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Efficient image compression with optimized biorthogonal wavelets

Efficient image compression with optimized biorthogonal wave...

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

作者： Hoffman, Michael D. Li, Shidong San Francisco State University Department of Mathematics 1600 Holloway San Francisco CA 94132

A new parameterization approach for the construction of biorthogonal wavelets has revealed the possibility of deriving optimized biorthogonal filterbanks. Such a design methodology incorporates various optimization criteria and the regularity requirement into a single procedure while maintaining the usual perfect reconstruction principle. Because of the parameterization, the additional design procedure becomes fundamentally an unconstrained optimization problem. The method provides examples of new biorthogonal dual filters of slightly shorter length with comparable performance characteristics to that of traditional biorthogonal dual filters of longer length. image coding.using such new filterbanks becomes more efficient while maintaining similar quality. Preliminary studies in image coding.will be reported in the presentation.

关键词： image compression

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A cryptanalysis procedure of the data encryption standard

A cryptanalysis procedure of the data encryption standard

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

作者： Silva G., Victor Manuel CIDETEC IPN Avenida Te #950 C.P. 08400 Mexico D.F. Mexico

In this paper an attack strategy on the data encryption Standard (DES) that is different from the existing ones is developed. The attack strategy is based on a theorem proved by the author, called LR theorem. The attack can be done by means of a personal computer, i.e. a Pentium IV based machine. Obviously, more information than a sample of plaintext and ciphertext is required. However, this additional requirement is reduced to a minimum of just 24 bits. The LR theorem uncovers 16 trapdoors of which 2 are of importance. With this knowledge, an attack on Triple-DES can be performed using the aforementioned personal computer. A simple solution to this kind of attack is proposed, preserving the complexity of the Triple-DBS, 2112.

关键词： Cryptography

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Exploiting the distributed source coding.paradigm for low-complexity compression of hyperspectral images

Exploiting the distributed source coding paradigm for low-co...

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

作者： Papini, David Barni, Mauro Abrardo, Andrea Garzelli, Andrea Magli, Enrico Department of Information Engineering University of Siena Italy Department of Electronics Politecnico di Torino Italy Department of Information Engineering University of Siena Via Roma 56 53100 - Siena Italy

The goal of this work is to study the feasibility of a low-complexity encoder for lossless compression of hyperspectral images. Since on-board bandwidth and power resources are limited for remote sensing systems, we adopted the distributed source coding.(DSC) paradigm as a starting point for moving the computational complexity from the encoder to the decoder. The advantages from locating a simple encoder on the aerial platform are far more relevant than the increased costs of a more complex decoder at the ground station. Two lossless compression algorithms have been developed, the former performing a scalar encoding.of the syndromes transmitted for each band of the hyperspectral image, the latter implementing a vectorial approach and yielding a slightly better compression ratio than the scalar one. No information about the spatial correlation is taken into account, while spectral correlation is explicitly exploited only at the decoder side. Experimental results confirm the asymmetrical distribution of computational complexity between encoder and decoder, with a strong increase of decoding.times although the recorded encoding.times are still higher than those achieved by JPEG-LS. As to the compression rate, our codecs perform very well compared to JPEG-LS or CALIC 2D, and worse than CALIC 3D, which also carries out inter-band decorrelation thus requiring a quite long processing time.

关键词： image coding

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Virtually lossless compression of scientific data: An application to astrophysical images

Virtually lossless compression of scientific data: An applic...

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

作者： Aiazzi, Bruno Alparone, Luciano Baronti, Stefano Lastri, Cinzia Nencini, Filippo Institute of Applied Physics Nello Carrara Via Panciatichi 64 50127 Firenze Italy Dept. Electron. and Telecoms. University of Florence Via Santa Marta 3 50139 Firenze Italy Dept. Information Engineering University of Siena Via Roma 56 53100 Siena Italy

This paper describes an image compression strategy potentially capable of preserving the scientific quality of astrophysical data, simultaneously allowing a consistent bandwidth reduction to be achieved. Unlike strictly lossless techniques, by which moderate compression ratios are attainable, and conventional lossy techniques, in which the mean squared error of the decoded data is globally controlled by user, near-lossless methods are capable to locally constrain the maximum absolute error, based on user's requirements. An advanced lossless/near-lossless differential pulse code modulation (DPCM) scheme, recently introduced by the authors and relying on a causal spatial prediction, is adjusted to the specific characteristics of astrophysical image data (high radiometric resolution, generally low noise, etc.). The background noise is preliminarily estimated to drive the quantization stage for high quality, which is the primary concern in most of astrophysical applications. Extensive experimental results of lossless, near-lossless, and lossy compression of astrophysical images acquired by the Hubble Space Telescope show the advantages of the proposed method compared to standard techniques like JPEG-LS and JPEG2000. Eventually, the rationale of virtually-lossless compression, that is a noise-adjusted lossles/near-lossless compression, is highlighted and found to be in accordance with concepts well established for the astronomers' community.

关键词： image compression

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Computational complexity of object-based image compression

Computational complexity of object-based image compression

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

作者： Schmalz, Mark S. Ritter, Gerhard X. Center for Computer Vision and Visualization University of Florida Gainesville FL 32611

image compression via transform coding.applied to small rectangular regions or encoding.blocks appears to be approaching asymptotic rate-distortion performance. However, an emerging compression technology, called object-based compression (OBC) promises significantly improved performance via compression ratios ranging from 200:1 to as high as 2,500:1. OBC involves segmentation of image regions, followed by efficient encoding.of each region's content and boundary. During decompression, such regions can be approximated by objects from a codebook, yielding a reconstructed image that is semantically equivalent to the corresponding source image, but has pixel- and featural-level differences. Semantic equivalence between the source and decompressed image facilitates fast decompression through efficient substitutions, albeit at the cost of codebook search in the compression step. Given small codebooks, OBC holds promise for information-push technologies where approximate context is sufficient, for example, transmission of surveillance images that provide the gist of a scene. However, OBC is not necessarily useful for applications requiring high accuracy, such as medical image processing, because substitution of source content can be inaccurate at small spatial scales. The cost of segmentation is a significant disadvantage in current OBC implementations. Several innovative techniques have been developed for region segmentation, as discussed in a previous paper [4]. Additionally, tradeoffs between representational fidelity, computational cost, and storage requirement occur, as with the vast majority of lossy compression algorithms. This paper analyzes the computational (time) and storage (space) complexities of several recent OBC algorithms applied to single-frame imagery. A time complexity model is proposed, which can be associated theoretically with a space complexity model that we have previously published [2]. The result, when combined with measurements of representationa

关键词： image compression

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