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检索条件"主题词=Compression Algorithms"

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Color image coding using wavelet pyramid coders

Color image coding using wavelet pyramid coders

引用

IEEE Southwest Symposium on Image Analysis and Interpretation

作者： Mitra, S Long, R Pemmaraju, S Muyshondt, R Thoma, G TEXAS TECH UNIV DEPT ELECT ENGNLUBBOCKTX 79409

ISBN: (纸本)0780332008

Despite the existence of the current standard for still image compression namely JPEG (Joint Photographic Experts Group), alternative techniques for image compression are being investigated due to the need for fast and high quality storage and transmission of large datasets for distribution through the Internet or in CD-ROM. The use of the wavelet transform for multi-resolution pyramid decomposition of images for data compression and transmission has already been successfully employed by a number of researchers using the common frame of linear subband filtering techniques. However, to achieve a desired compression ratio for a specific class of images, an optimized compression algorithm needs to be developed by considering all stages, i.e. from initial transform mapping to final encoding. This paper addresses the suitability and requirement of further development of a wavelet pyramid coding in compressing color images, specifically the color Visible Human digital photographic dataset. The distinct advantages of a newly developed adaptive vector quantization (VQ) over commonly used scalar quantization and conventional VQ of the wavelet decomposed error pyramids are also discussed.

关键词： color image coding Data compression Image compression JPEG scalar quantization compression algorithms wavelets compression ratio Vector quantization ENCODER storage stability wavelet transforms

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A parallel implementation of a fractal image compression algorithm

A parallel implementation of a fractal image compression alg...

引用

Southeastern Symposium on System Theory

作者： W.A. Stapleton W. Mahmoud D.J. Jackson Department of Electrical Engineering University of Alabama Tuscaloosa AL USA

Presented in this paper are experimental results for a parallel implementation of a fractal image compression algorithm. The fractal image compression process exhibits a natural parallelism and the specific parallel implementation is shown to be beneficial for the execution speed of the algorithm. Furthermore, computational speed has been enhanced through an algorithmic modification employing a quadtree recomposition approach in which quadtree subblocks are iteratively combined into larger ranges for fractal encoding. Furthermore, classification schemes which serve to reduce the O(n/sup 4/) algorithmic complexity are explored.

关键词： Fractals Image coding Iterative algorithms Pipelines Testing Parallel processing Discrete cosine transforms compression algorithms Decoding Image quality

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Data compression using encrypted text

Data compression using encrypted text

引用

International Forum on Research and Technology Advances in Digital Libraries (ADL)

作者： R. Franceschini A. Mukherjee Department of Computer Science University of Central Florida Orlando FL USA

We present an algorithm for text compression. The basic idea of our algorithm is to define a unique encryption or signature of each word in the dictionary by replacing certain characters in the words by a special character "*" and retaining a few characters so that the word is still retrievable. For any encrypted text the most frequently used character is "*" and the standard compression algorithms can exploit this redundancy in an effective way. We advocate the following compression paradigm: given a compression algorithm A and a text T, we apply the same algorithm A on an encrypted text *T and retrieve the original text via a dictionary which maps the decompressed text *T to the original text T. We report better results for most widely used compression algorithms such as Huffman, LZW, arithmetic, unix compress, gnu-zip with respect to a text corpus. The compression rates using these algorithms are much better than the dictionary based methods reported in the literature. One basic assumption of our algorithm is that the system has access to a dictionary of words used in all the texts along with a corresponding "cryptic" dictionary. The cost of this dictionary is amortized over the compression savings for all the text files handled by the organization. If two organizations wish to exchange information using our compression algorithm, they must share a common dictionary. We compare our methods with other dictionary based methods and present future research problems.

关键词： Data compression Cryptography Dictionaries compression algorithms Costs Computer science Arithmetic Memory Bandwidth Explosions

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Speech signal compression using sub-band division and sub-adaptive polynomial mapping quantization

Speech signal compression using sub-band division and sub-ad...

引用

IEEE Region 10 International Conference TENCON

作者： H. Saito S. Nakamura Department of Electronic Engineering Tokyo Denki University Japan

Data compression techniques, such as image compression and speech compression, are useful in communication applications. We propose a simple speech compression algorithm using sub-band division and polynomial mapping quantization made from the piecewise linear quantization function for a voice-mail system. The voice-mail is an audio equivalent of sending letters. The main differences are that computer networks deliver the mail instead of a postman, and that electronic recording is used instead of a postman. Although speech data are stored in a semiconductor memory device, its capacity and the available network capacity are limited. Therefore, it is necessary to compress the data as much as possible. However there are two conditions to be satisfied: one is that the reconstructed data must be understood correctly. The other is that we must identify the sender. Signals with a rate of 64 kbit/sec are compressed at a ratio of about 1/13 using the proposed sub-band division and polynomial mapping quantization.

关键词： Speech Image coding Quantization Polynomials Voice mail Data compression Application software compression algorithms Piecewise linear techniques Computer networks

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Efficient lossless compression of trees and graphs

Efficient lossless compression of trees and graphs

引用

Data compression Conference (DCC)

作者： Shenfeng Chen J.H. Reif Department of Computer Science Duke University Durham NC USA

Summary form only given, as follows. Data compression algorithms have been widely used in many areas to meet the demand of storage and transfer of large size data. Most of the data compression algorithms regard the input as a sequence of binary numbers and represent the compressed data also as a binary sequence. However, in many areas such as programming languages (e.g. LISP and C) and compiler design, it is more desirable to have a compression algorithm which compresses a data structure while keeping a similar structure of the original data in the compressed form. In addition to reducing storage space, such compression also has the benefit of efficiently executing various operations (e.g. searching) in the compressed form. We study the problem of compressing a non-binary data structure (e.g. tree, undirected and directed graphs) in an efficient way while keeping a similar structure in the compressed form. To date, there has been no proven optimal algorithm for this problem. We use the idea of building LZW tree in LZW compression to compress a binary tree generated by a stationary ergodic source. The tree is parsed into subtrees using breadth first search and an optimal dictionary is constructed with each index pointing to a distinct subtree. We replace the parsed subtrees by dictionary indices to formed the compressed tree. We also extend our tree compression algorithm to compress undirected and directed acyclic graphs.

关键词： Tree graphs Data compression compression algorithms Dictionaries Binary sequences Computer languages Algorithm design and analysis Data structures Tree data structures Buildings

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A nonlinear adaptive predictor for speech compression

A nonlinear adaptive predictor for speech compression

引用

International Conference on Neural Networks

作者： S. Hunt Department of Electrical and Computer Engineering University of Puerto Rico Mayaguez Puerto Rico

A neural nonlinear predictor for one dimensional signals is presented. It is based on a combination of linearization and QR decomposition that allows a fast adapting algorithm. The predictor is used in a speech compression algorithm that has proven to be superior to linear based models. The compression and training are done simultaneously, allowing the network to continually adapt to the signal. The results presented show that this algorithm outperforms a typical LPC coding algorithm.

关键词： compression algorithms Neural networks Linear predictive coding Speech coding Vector quantization Nonlinear equations Joining processes Predictive models Stochastic resonance Bit rate

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An information theoretic model for adaptive lossy compression

An information theoretic model for adaptive lossy compressio...

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IEEE Convention of the Electrical and ELectronic Engineers in Israel

作者： R. Zamir K. Rose Department Electrical Engineering Systems Tel-Aviv University Tel-Aviv Israel Department of ECE University of California Santa Barbara CA USA

We investigate the underlying mechanism of universal sequential, fixed distortion, lossy source coding algorithms, through the "eyes" of a random code. We model the adaptive codebook as a "mixed type" random code whose codeword type distribution evolves with time while its dimension goes to infinity. The evolution law in our model has a structure of a tree; a type inherits its frequency in the code from its parent-types matching probabilities. We find that this mechanism naturally selects the "good" codeword types for compressing the (unknown) source. As a consequence, the code becomes optimal for the source, and approaches the rate-distortion function as the time, and hence the dimension, go to infinity. Beyond its analytical interest, this model also provides guidelines for developing lossy string matching (Lempel-Ziv-like) algorithms.

关键词： H infinity control Frequency Algorithm design and analysis compression algorithms Source coding Pressing Rate-distortion Speech analysis Guidelines Speech coding

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Image compression with modified LZ77 coding

Image compression with modified LZ77 coding

引用

International Conference on Signal Processing Proceedings (ICSP)

作者： H. Nagumo Mi Lu K. Watson Department of Electrical Engineering Texas A and M University College Station TX USA

We present a new coding method for lossless gray-scale image compression. The method is based on modifications of LZ77-based compression and estimation of prediction errors of pixels. The method gives compression comp... 详细信息

关键词： Image coding Pattern matching Transform coding Gray-scale Arithmetic Estimation error Huffman coding Head compression algorithms Pixel

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Ultrasound image compression exploiting image formation models

Ultrasound image compression exploiting image formation mode...

引用

IEEE Symposium (IUS) Ultrasonics

作者： R.M. Cramblitt K.J. Parker Rochester Center for Biomedical Ultrasound Department of Electrical Engineering Rochester University of Rochester Rochester NY USA

The diagnostic benefits of teleradiology may not be available in locations which lack high-bandwidth transmission channels. In these cases, data compression is required in order to use low bit-rate digital channels. Standard compression algorithms, such as JPEG, are not ideally suited to ultrasound images, in which speckle structure plays an important role. We have developed an algorithm for progressively encoding ultrasound images which incorporates knowledge of both the system parameters and the image formation process, and which preserves the speckle structure in the image. The algorithm operates on the digitized RF output of an ultrasound scanner and identifies pixels in the image giving rise to the largest output in a local neighborhood. It iteratively allocates point scatterers to these pixels and transmits their amplitudes and locations using Huffman encoding. The image is reconstructed by convolving an RF pulse with the received sparse scatterer matrix. We describe the basic algorithm and compare its performance, using rate-distortion curves, to the JPEG standard. Distortion is measured by both simple root-mean-squared (RMS) error and human visual system (HVS)-weighted RMS error. The HVS distortions are included to better account for the perceived differences in image quality seen by the diagnostician.

关键词： Ultrasonic imaging Image coding Speckle Iterative algorithms Radio frequency Scattering Data compression compression algorithms Transform coding Radiofrequency identification

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A new quantization algorithm for a wavelet compression scheme of coronary angiograms

A new quantization algorithm for a wavelet compression schem...

引用

Computers in Cardiology (CinC)

作者： A. Bezerianos A. Munteanu P. Cristea D. Alexopoulos Department of Medical Physics University of Patras Patras Greece Department of D.S.P. Technical University of Bucharest Bucharest Romania Division of Cardiology Medical School University of Patras Patras Greece

New methods for image compression which are able to store and retrieve efficiently the images produced by a digital angiographic unit are needed for clinical use. Currently discrete cosine transform (DCT) based compression schemes (i.e. JPEG, MPEG) generate unacceptable block artefacts in coronary angiograms at high compression ratios, because of the block coefficients quantization. We propose a wavelet compression algorithm that overcomes fundamentally this drawback. Using a set of 40 coronary angiograms, we evaluated the method by analyzing several image quality factors: peak signal to noise ratio, compression ratio, maximum absolute difference and mean difference of gray levels and subjective evaluation. At the same compression ratio, the proposed technique outperforms the JPEG method in image quality presentation.

关键词： Quantization Image coding Transform coding Discrete cosine transforms Image quality Image retrieval compression algorithms Image analysis Signal analysis PSNR

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