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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71-80 订阅

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A new video coder powered with second generation wavelets

A new video coder powered with second generation wavelets

引用

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

作者： Brangoulo, S Gioia, P Laurent, N Fournier, J France Telecom R&D F-35512 Cesson Sevigne France

ISBN: (纸本)0819450812

In this paper we propose a new method based on Second Generation Wavelets (SGW), a recently emerged mathematic transform, already successfully applied in 3d coding. This new wavelet transform (SGW) applied to meshes is performed using the powerful lifting scheme, keeping the main features of the first generation wavelets whilst introducing some useful properties such as: analysis on general domains (typically arbitrary, non linear domains of R-n), adapted basis for weighted approximation/interpolation and weighted measure and transform adapted to irregular sampled data. Thus in this paper we propose a video coder based on second generation wavelet theory and mesh geometry. In fact, we focus on video coder error images which are mainly composed of high frequencies and singularities, i.e. typically the kind of data that second generation wavelet can successfully process. The main advantage is that these wavelets can be designed to fit exactly on singularities, shapes, textures, and edges. Hence, we can further reduce redundancy and improve coding.efficiency over those peculiar settings.

关键词： second generation wavelets lifting video compression meshes

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data compression trade-offs in sensor networks

Data compression trade-offs in sensor networks

引用

7th Conference on mathematics of data/image coding. compression, and encryption

作者： Chen, M Fowler, ML SUNY Binghamton Dept Elect & Comp Engn Binghamton NY 13902 USA

ISBN: (纸本)0819454990

This paper first discusses the need for data compression within sensor networks and argues that data compression is a fundamental tool for achieving trade-offs in sensor networks among three important sensor network parameters: energy-efficiency, accuracy, and latency. Next, it discusses how to use Fisher information to design data compression algorithms that address the trade-offs inherent in accomplishing multiple estimation tasks within sensor networks. Results for specific examples demonstrate that such trades can be made using optimization frameworks for the data compression algorithms.

关键词： data compression sensor networks estimation Fisher information emitter location time-difference-of-arrival TDOA frequency-difference-of-arrival FDOA

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Techniques for region coding.in object-based image compression

Techniques for region coding in object-based image compressi...

引用

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

作者： Schmalz, MS Univ Florida Dept Comp & Informat Sci & Engn Gainesville FL 32611 USA

ISBN: (纸本)0819450812

Object-based compression (OBC) is an emerging technology that combines region segmentation and coding.to produce a compact representation of a digital image or video sequence. Previous research has focused on a variety of segmentation and representation techniques for regions that comprise an image. The author has previously suggested [1] partitioning of the OBC problem into three steps: (1) region segmentation, (2) region boundary extraction and compression, and (3) region contents compression. A companion paper [2] surveys implementationally feasible techniques for boundary compression. In this paper, we analyze several strategies for region contents compression, including lossless compression, lossy VPIC, EPIC, and EBLAST compression, wavelet-based coding.(e.g., JPEG-2000), as well as texture matching approaches. This paper is part of a larger study that seeks to develop highly efficient compression algorithms for still and video imagery, which would eventually support automated object recognition (AOR) and semantic lookup of images in large databases or highvolume OBC-format datastreams. Example applications include querying journalistic archives, scientific or medical imaging, surveillance image processing and target tracking, as well as compression of video for transmission over the Internet. Analysis emphasizes time and space complexity, as well as sources of reconstruction error in decompressed imagery.

关键词： image compression image segmentation computational complexity

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Meitei coding.for subband image compression

Meitei coding for subband image compression

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

作者： Singh, YK Indian Statistical Institute (India)

ISBN: (纸本)0819450812

Proposed here is a coding.scheme based on a 2-dimensional spatial tree entitled 2-MT (2-dimensional Meitei Tree). In this tree structure, we take the element of the upper left corner as the root. From the next level onwards, there are three nodes in each level, namely, left node, middle node and right node. The left and the right nodes are connected to the middle node. Each middle node is connected to the middle node of the next lower level. In other words, only middle nodes have two branches, the right node and the left node. This tree structure is easy to generate and manipulate a matrix (square or rectangular) easily. This avoids. the necessity to make the size of an image matrix square and of power 2, as in SPIHT (Set Partitioning in Hierarchical Tree). Also, from the coding.implementation point of view, it is much simpler as compared to SPIHT. The corresponding coding.scheme based on 2-MT will be known Meitei coding.which will be used in our subband compression scheme. This coding.scheme is much more flexible and higher compression ratio can be achieved as compared to SPIHT.

关键词： lossy compression subband transforms spatial tree 2-dimensional Meitei tree node-matrix sub-matrix Meitei coding SPIHT-coding sorting pass refinement pass

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Higher-dimensional wavelet transforms for hyperspectral data compression and feature recognition

Higher-dimensional wavelet transforms for hyperspectral data...

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

作者： Scholl, JF Dereniak, EL Univ Arizona Ctr Opt Sci Tucson AZ 85721 USA

ISBN: (纸本)0819450812

The dominant image processing tasks for hyperspectral data are compression and feature recognition. These tasks go hand-in-hand. Hyperspectral data contains a huge amount of information that need to be processed (and often very quickly) depending on the application. The discrete wavelet transform is the ideal tool for this type of data structure. There are applications that require such processing (especially feature recognition or identification) be done extremely fast and efficiently. Furthermore the higher number of dimensions implies a number of different ways to do these transforms. Much of the work in this area to the present time has been focused on JPEG2000 type compression of each component image involving fairly sophisticated coding.techniques;relatively little attention has been paid to other configurations of wavelet transforms of such data, as well as rapid feature identification where compression may not be necessary at all. This paper describes other versions of the 3D wavelet transform that allow the resolution in both the spatial domain and spectral domain to be adjusted separately. Other issues associated with low complexity feature recognition with and without compression using versions of the 3D hyperspectral wavelet transforms will be discussed along with some illustrative calculations.

关键词： discrete wavelet transforms hyperspectral imaging feature recognition compression

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Boundary representation techniques for object-based image compression

Boundary representation techniques for object-based image co...

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

作者： Schmalz, MS Ritter, GX Univ Florida Ctr Comp Vis & Visualizat Gainesville FL 32611 USA

ISBN: (纸本)0819450812

As digital image and video compression technology evolves, it appears that transform based coding.or compression techniques will reach asymptotic rate-distortion performance, especially with respect to linear transforms. Although nonlinear compression techniques (for example, based on Markov models) are being developed, progress has been relatively slow due to challenges in theory development. Alternatively, several research teams have produced algorithms for object-based compression (OBC), whereby an image is segmented into areas of similar color or spatial variance. Each segmented region can then be represented in terms of a small region descriptor and somewhat less compact set of boundary descriptors. This paper examines boundary representations and complexity measures for OBC - a previous publication [1], also related to OBC, overviewed region segmentation techniques. Of particular interest ot OBC is the evolution of boundary representations from early approaches such as chain coding.or simplicial complexes to transform coded descriptors such as Fourier or wavelet-based representations. These techniques precede more modem methods such as hierarchical transforms (e.g., wavelets) and direct compression of Boolean boundary representations. In this paper, the authors develop boundary compression algorithms based on concepts derived from statistical image compression theory and hierarchical codebook representations. The resulting boundary encoding.technique is suitable for a wide range of compression applications, in particular, OBC. Performance criteria include computational complexity of the encoding.process, as well as space complexity of intermediate and final boundary representations.

关键词： object-based image compression boundary representation complexity analysis

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Region segmentation techniques for object-based image compression - A review

Region segmentation techniques for object-based image compre...

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7th Conference on mathematics of data/image coding. compression, and encryption

作者： Schmalz, MS Ritter, GX Univ Florida Ctr Comp Vis & Visualizat Gainesville FL 32611 USA

ISBN: (纸本)0819454990

image compression based on transform coding.appears to be approaching an asymptotic bit rate limit for application-specific distortion levels. However, a new compression technology, called object-based compression (OBC) promises improved rate-distortion performance at higher compression ratios. OBC involves segmentation of image regions, followed by efficient encoding.of each region's content and boundary. Advantages of OBC include efficient representation of commonly occurring textures and shapes in terms of pointers into a compact codebook of region contents and boundary primitives. This facilitates fast decompression via substitution, at the cost of codebook search in the compression step. Segmentation cose and error are significant disadvantages in current OBC implementations. Several innovative techniques have been developed for region segmentation, including (a) moment-based analysis, (b) texture representation in terms of a syntactic grammar, and (c) transform coding.approaches such as wavelet based compression used in MPEG-7 or JPEG-2000. Region-based characterization with variance templates is better understood, but lacks the locality of wavelet representations. In practice, tradeoffs are made between representational fidelity, computational cost, and storage requirement. This paper overviews current techniques for automatic region segmentation and representation, especially those that employ wavelet classification and region growing techniques. Implementational discussion focuses on complexity measures and performance metrics such as segmentation error and computational cost.

关键词： object-based image compression region segmentation complexity analysis

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Benchmarking techniques for evaluation of compression transform performance in ATR applications

Benchmarking techniques for evaluation of compression transf...

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7th Conference on mathematics of data/image coding. compression, and encryption

作者： Schmalz, MS Univ Florida Dept Comp & Informat Sci & Engn Gainesville FL 32611 USA

ISBN: (纸本)0819454990

image compression is increasingly employed in applications such as medical imaging, for reducing data storage requirement, and Internet video transmission, to effectively increase channel bandwidth. Similarly, military applications such as automated target recognition (ATR) often employ compression to achieve storage and communication efficiencies, particularly to enhance the effective bandwidth of communication channels whose throughput suffers, for example, from overhead due to error correction/detection or encryption. In the majority of cases, lossy compression is employed due the resultant low bit rates (high compression ratio). However, lossy compression produces artifacts in decompressed imagery that can confound ATR processes applied to such imagery, thereby reducing the probability of detection (Pd) and possibly increasing the rate or number of false alarms (Rfa or Nfa). In this paper, the authors' previous research in performance measurement of compression transforms is extended to include (a) benchmarking algorithms and software tools, (b) a suite of error exemplars that are designed to elicit compression transform behavior in an operationally relevant context, and (c) a posteriori analysis of performance data. The following transforms are applied to a suite of 64 error exemplars: Visual Pattern image coding.(VPIC [1]), Vector Quantization with a fast codebook search algorithm (VQ [2,3]), JPEG and a preliminary implementation of JPEG 2000 [4,5], and EBLAST [6-8]. compression ratios range from 2:1 to 200:1, and various noise levels and types are added to the error exemplars to produce a database of 7,680 synthetic test images. Several global and local (e.g., featural) distortion measures are applied to the decompressed test imagery to provide a basis for rate-distortion and rate-performance analysis as a function of noise and compression transform type.

关键词： image compression error measurement automated target recognition

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Advanced methods for onboard lossless compression of hyperspectral data

Advanced methods for onboard lossless compression of hypersp...

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

作者： Aiazzi, B Alparone, L Baronti, S Bertoli, A Lastri, C Lotti, F Magli, E Olmo, G Penna, B CNR IFAC Inst Appl Phys Nello Carrara I-50127 Florence Italy

ISBN: (纸本)0819450812

This paper reports about the main results of a project aimed at developing advanced methods for lossless compression of hyperspectral data and at providing implementations on a space-certified processing board. In particular, adaptive DPCM methods exploiting 3D spectral correlation and context-based entropy coding.are compared. The algorithms considered utilize "classified" DPCM, where predictors are preliminarily calculated, taking into account the statistical properties of the image being compressed, and then adaptively selected or combined. Starting from a few advanced algorithms recognized as the most relevant, a scheme suitable for onboard implementation has been derived and implemented on a TSC21020 board. The final method developed represents a good compromise between compression results and computational complexity and utilizes a CCSDS Rice encoder. Performances are assessed by means of comparisons with the results obtained by both standard and advanced algorithms providing state-of-the-art and top performances, respectively.

关键词： Band-Interleaved by Line (BIL) computational complexity CCSDS rice encoder Differential Pulse Code Modulation (DPCM) hyperspectral imagery interframe prediction lossless data compression satellite remote sensing

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Phase signature-based image authentication watermark robust to compression and coding

Phase signature-based image authentication watermark robust ...

引用

7th Conference on mathematics of data/image coding. compression, and encryption

作者： Ahmed, F Moskowitz, IS Catholic Univ Amer Dept EECS Washington DC 20064 USA

ISBN: (纸本)0819454990

We present the further development of a watermarking technique that embeds an authentication signal in an image. In this paper, we concentrate on the JPEG 2000 image format. The detection/extraction of this signal can,then be used to decide whether the image has gone through any intentional malicious tampering. Therefore, the watermark needs to be fragile to such tampering attacks. On the other hand, we need to make sure that the authentication is robust to change resulting from the watermarking process itself, or from necessary changes such as image compression. We address the robustness against watermarking process issue in two ways. First, we decompose the image into phase and magnitude values. A signature is then generated from the phase values. In particular, binary phase-only filters and their variants will are utilized for this. This signature is subsequently hidden into the magnitude part by a bit-plane embedding technique. The disjoint operations of signature generation and signature embedding minimize the embedding artifacts of the authentication signal. Secondly, we use wavelet decomposition, whereby, the signature can be generated from one subband, and then it can be embedded in other subband(s), or the same subband.

关键词： authentication wavelet JPEG 2000 watermarking correlation Phasemark (TM)

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