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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61-70 订阅

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Error measures for object-based image compression

Error measures for object-based image compression

引用

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 based on transform coding.appears to be approaching a bit-rate limit for visually acceptable distortion levels. Although an emerging compression technology called object-based compression (OBC) promises significantly improved bit rate and computational efficiency, OBC is epistemologically distinct in a way that renders existing image quality measures (IQMs) for compression transform optimization less suitable for OBC. In particular, OBC segments source image regions, then efficiently encodes each region's content and boundary. During decompression, region contents are often replaced by similar-appearing objects from a codebook, thus producing a reconstructed image that corresponds semantically to the source image, but has pixel-, featural-, and object-level differences that are apparent visually. OBC thus gains the advantage of fast decompression via efficient codebook-based substitutions, albeit at the cost of codebook search in the compression step and significant pixel- or region-level errors in decompression. Existing IQMs are pixel- and region-oriented, and thus tend to indicate high error due to OBC's lack of pixel-level correlation between source and reconstructed imagery. Thus, current IQMs do not necessarily measure the semantic correspondence that OBC is designed to produce. This paper presents image quality measures for estimating semantic correspondence between a source image and a corresponding OBC-decompressed image. In particular, we examine the semantic assumptions and models that underlie various approaches to OBC, especially those based on textural as well as high-level name and spatial similarities. We propose several measures that are designed to quantify this type of high-level similarity, and can be combined with existing IQMs for assessing compression transform performance. Discussion also highlights how these novel IQMs can be combined with time and space complexity measures for compression transform optimization.

关键词： image compression

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Near-lossless compression of hyperspectral data through classified spectral prediction

Near-lossless compression of hyperspectral data through clas...

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

作者： Aiazzi, Bruno Alparone, Luciano Baronti, Stefano Garzelli, Andrea Lastri, Cinzia Santurri, Leonardo Institute of Applied Physics Nello Carrara IFAC-CNR 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 presents a novel scheme for lossless/near-lossless hyperspectral image compression, that exploits a classified spectral prediction. MMSE spectral predictors are calculated for small spatial blocks of each band and are classified (clustered) to yield a user-defined number of prototype predictors for each wavelength, capable of matching the spatial features of different classes of pixel spectra. Unlike most of the literature, the proposed method employs a purely spectral prediction, that is suitable for compressing the data in band-interleaved-by-line (BIL) format, as they are available at the output of the on-board spectrometer. In that case, the training phase, i.e., clustering of predictors for each wavelength, may be moved off-line. Thus, prediction will be slightly less fitting, but the overhead of predictors calculated on-line is saved. Although prediction is purely spectral, hence ID, spatial correlation is removed by the training phase of predictors, aimed at finding statistically homogeneous spatial classes matching the set of prototype spectral predictors. Experimental results on AVIRIS data show improvements over the most advanced methods in the literature, with a computational complexity far lower than that of analogous methods by other authors.

关键词： image compression

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Double random phase spread spectrum spread space technique for secure parallel optical multiplexing with individual encryption key

Double random phase spread spectrum spread space technique f...

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

作者： Hennelly, B.M. Javidi, B. Sheridan, J.T. Department of Electronic and Electrical Engineering Faculty of Engineering and Architecture University College Dublin Belfield Dublin 4 Ireland Department of Electrical and Computer Engineering University of Connecticut Storrs CT 06269-2157

A number of methods have been recently proposed in the literature for the encryption of 2-D information using linear optical systems. In particular the double random phase encoding.system has received widespread attention. This system uses two Random Phase Keys (RPK) positioned in the input spatial domain and the spatial frequency domain and if these random phases are described by statistically independent white noises then the encrypted image can be shown to be a white noise. Decryption only requires knowledge of the RPK in the frequency domain. The RPK may be implemented using a Spatial Light Modulators (SLM). In this paper we propose and investigate the use of SLMs for secure optical multiplexing. We show that in this case it is possible to encrypt multiple images in parallel and multiplex them for transmission or storage. The signal energy is effectively spread in the spatial frequency domain. As expected the number of images that can be multiplexed together and recovered without loss is proportional to the ratio of the input image and the SLM resolution. Many more images may be multiplexed with some loss in recovery. Furthermore each individual encryption is more robust than traditional double random phase encoding.since decryption requires knowledge of both RPK and a lowpass filter in order to despread the spectrum and decrypt the image. Numerical simulations are presented and discussed.

关键词： Spread spectrum communication

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Fractal based techniques and their applications

Fractal based techniques and their applications

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作者： Lai, Cheung-Ming Hong Kong Polytechnic University (Hong Kong)

学位级别：Ph.D.

The aim of this research is to develop efficient algorithms for fractal image coding. which can be applied in digital image compression, image magnification and image denoising. Fractal image coding.can provide a highly reconstructed image quality with a high compression ratio, is independent of resolution, and has a fast decoding.process. The problem with fractal coding.is its high computational complexity in the encoding.process. Most of the encoding.time is spent finding the best-matched domain block from a large domain pool to represent an input range block with respect to contrast and intensity offset, as well as the isometry transformations. The objectives of this research are to investigate and develop efficient techniques for fractal image coding. fractal-based image magnification and denoising. In this thesis, four efficient fractal image-coding.algorithms have been proposed. The first algorithm is based on new feature vectors and the property of zero contrast. The proposed feature vectors can provide a better representation of image blocks, and thus result in a more efficient search of the domain block. The second algorithm is an efficient windowing scheme for fractal image coding.based on the local variances method. In our method, windows covering those domain blocks whose variances are higher than that of the range block are considered according to a mathematical model. The exhaustive search algorithm can obtain the optimal result by searching all the blocks within the domain pool, but this process requires a high computational cost, which limits its practical application. A single kick-out condition is proposed which can avoid a large number of range-domain block matches when finding the best-matched domain block. An efficient method for zero contrast prediction is also proposed, which can determine whether the contrast factor for a domain block is zero or not, and compute the corresponding difference between the range block and the transformed domain b

关键词： Hong Kong Polytechnic University -- Dissertations. image compression. image processing -- Digital techniques -- mathematics. Fractals. data encryption (Computer science)

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

Proceedings of SPIE - Mathematics of Data/Image Coding, Comp...

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

The proceedings contain 16 papers from the Proceedings of SPIE - mathematics of data/image coding. compression, and encryption VII, with Applications. The topics discussed include: autosophy data/image compression and encryption;region segmentation techniques for object-based image compression: a review;data compression trade-offs in sensor networks;the relationship between shape under similarly transformations and shape under affine transformations;sparsity prediction and application to a new steganographic technique;phase signature-based image authentication watermark robust to compression and coding.texture-based steganalysis: results for color images;and combined data encryption and compression using chaos functions.

关键词： image compression

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Proceedings of SPIE: mathematics of data/image coding. compression, and encryption VI, With Applications

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

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

The proceedings contains 22 papers of SPIE : mathematics of data/image coding. compression, and encryption VI, with applications. The topics discussed include: natural language insensitive short textual string compression;techniques for region coding.in object-based image compression;boundary representation techniques for object-based image compression;meitei coding.for subband image compression;standards-compatible compression for automated image recognition in sensor networks and surveillance systems and non-MSE data compression for emitter location for radar pulse trains.

关键词： image compression

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mathematics of data/image coding. compression, and encryption Vii, With Applications (Proceedings of S P I E)

Mathematics Of Data/image Coding, Compression, And Encryptio...

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2004年

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mathematics of data/image coding. compression, and encryption Vi, With Applications (Proceedings of Spie, 5208)

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

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2004年

作者： Mark Steven Schmalz

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Combined data encryption and compression using chaos functions

Combined data encryption and compression using chaos functio...

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

作者： Bose, R Pathak, S Indian Inst Technol Dept Elect Engn New Delhi 110016 India

ISBN: (纸本)0819454990

Past research in the field of cryptography has not given much consideration to arithmetic coding.as a feasible encryption technique, with studies proving compression-specific arithmetic. coding.to be largely unsuitable for encryption. Nevertheless, adaptive modelling, which offers a huge model, variable in structure, and as completely as possible a function of the entire text that has been transmitted since the time the model was initialised, is a suitable candidate for a possible encryption-compression combine. The focus of the work presented in this paper has been to incorporate recent results of chaos theory, proven to be cryptographically secure, into arithmetic coding. to devise a convenient method to make the structure of the model unpredictable and variable in nature, and yet to retain, as far as is possible, statistical harmony, so that compression is possible. A chaos-based adaptive arithmetic coding.encryption technique has been designed, developed and tested and its implementation has been discussed. For typical text files, the proposed encoder gives compression between 67.5% and 70.5%, the zero-order compression suffering by about 6% due to encryption, and is not susceptible to previously carried out attacks on arithmetic coding.algorithms.

关键词： symmetric key cryptography variable model arithmetic coding chaos compression encryption

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Autosophy data/image compression and encryption

Autosophy data/image compression and encryption

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

作者： Holtz, K Holtz, E Kalienky, D Autosophy San Francisco CA 94108 USA

ISBN: (纸本)0819454990

Multimedia data may be transmitted or stored either according to the classical Shannon information theory or according to the newer Autosophy information theory. Autosophy algorithms combine very high "lossless" data and image compression with virtually unbreakable "codebook" encryption. Shannon's theory treats all data items as "quantities", which are converted into binary digits (bit), for transmission in meaningless bit streams. Only "lossy" data compression is possible. A new "Autosophy" theory was developed by Klaus Holtz in 1974 to explain the functioning of natural self-assembling structures, such as chemical crystals or living trees. The same processes can also be used for growing self-assembling data structures, which grow like data crystals or data trees in electronic memories. This provides true mathematical learning algorithms, according to a new Autosophy information theory. Information in essence is only that which can be perceived and which is not already known by the receiver. The transmission bit rates are dependent on the data content only. Applications already include the V.42bis compression standard in modems, the gif and tif formats for lossless image compression, and Autosophy Internet television. A new 64bit data format could make all future communications compatible and solve the Internet's Quality of Service (QoS) problems.

关键词： autosophy information theory data compression image compression encryption Internet video quality of service (QoS)

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