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检索条件"主题词=Compression Algorithms"

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Real time implementation concerns for lossless waveform compression

Real time implementation concerns for lossless waveform comp...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： F. Livinston N. Magotra S. Stearns W. McCoy Dept. of Electr. Eng. & Comput. Eng. New Mexico Univ. Albuquerque NM USA Department of EECE University of New Mexico Albuquerque NM USA

Lossless waveform data compression is useful in application areas where the fidelity of the signal being compressed is critical, This paper presents a two stage lossless seismic waveform data compression algorithm and a discussion of various issues related to the algorithm's real time implementation. The first stage of the algorithm performs lossless adaptive prediction using a recursive least squares lattice (RLSL) while the second stage performs arithmetic coding. The RLSL uses an a priori algorithm and floating-point operations. The second stage of the algorithm uses an arithmetic coding algorithm that is capable of encoding 14 bit residue sequences. The algorithm was implemented in real time on a Texas Instruments TMS320C30 chip.

关键词： Image coding Lattices compression algorithms Data compression Least squares methods Arithmetic Convergence Laboratories Instruments Audio compression

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The effect of non-greedy parsing in Ziv-Lempel compression methods

The effect of non-greedy parsing in Ziv-Lempel compression m...

引用

Data compression Conference (DCC)

作者： R.N. Horspool Department of Computer Science University of Victoria Victoria BC Canada

Most practical compression methods in the LZ77 and LZ78 families parse their input using a greedy heuristic. However the popular gzip compression program demonstrates that modest but significant gains in compression performance are possible if non-greedy parsing is used. Practical implementations for using non-greedy parsing in LZ77 and LZ78 compression are explored and some experimental measurements are presented.

关键词： Dictionaries Encoding Computer science Performance gain Data compression Modems compression algorithms

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Quadtree based JBIG compression

Quadtree based JBIG compression

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Data compression Conference (DCC)

作者： B. Fowler R. Arps A. El Gamal D. Yang ISL Stanford University Stanford CA USA IBM Almaden Research Center San Jose CA USA

A JBIG compliant, quadtree based, lossless image compression algorithm is described. In terms of the number of arithmetic coding operations required to code an image, this algorithm is significantly faster than previous JBIG algorithm variations. Based on this criterion, our algorithm achieves an average speed increase of more than 9 times with only a 5% decrease in compression when tested on the eight CCITT bi-level test images and compared against the basic non-progressive JBIG algorithm. The fastest JBIG variation that we know of, using "PRES" resolution reduction and progressive buildup, achieved an average speed increase of less than 6 times with a 7% decrease in compression, under the same conditions.

关键词： Image coding Arithmetic Testing Image resolution Image sensors Power system reliability compression algorithms Circuits Data structures Facsimile

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An improved direct inverse problem solver for fractal interpolation functions with applications to signal compression

An improved direct inverse problem solver for fractal interp...

引用

URSI International Symposium on Signals, Systems, and Electronics (ISSSE)

作者： Jiangtao Wen Xuelong Zhu Computer and Information Division Department of Electronic Engineering Tsinghua University Beijing China

ISBN: (纸本)0780325168

A novel direct algorithm used to estimate parameters of fractal interpolation functions is proposed, and test results of its robustness and its signal compression performance are reported. The IFS fractal interpolation function (FIF) is becoming an increasingly appealing class of models of such signals as the height distribution of sea floors, seismograph, and electrocardiograph signals, due to its inherent advantages. Existing FlF-based signal compression algorithms usually use the FIF parameter estimation formula proposed by Uazel and Hayes (see IEEE Trans. Signal Processing, vo1.40, no.7, p.1724, 1992), which is based on least square-error fitting techniques and needs to calculate the derivatives of such a error measure with respect to FIF parameters. It is very inconvenient to introduce many other useful error measures in real signal processing applications, such as the Kullback entropy or the Hausdorff distance, for they may endanger the computability of the derivatives. A computationally efficient, direct algorithm for solving the inverse problem of the IFS interpolation signals is proposed. It can solve the FIF parameters from its samples without calculating the error function's derivatives. The algorithm's robustness in parameter estimation and usefulness in signal compression are shown with experimental results.

关键词： Inverse problems Fractals Interpolation Signal processing algorithms Parameter estimation Robustness Sea measurements Testing Sea floor compression algorithms

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Encoding mismatch in lossy source compression

Encoding mismatch in lossy source compression

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IEEE Convention of the Electrical and ELectronic Engineers in Israel

作者： A. Lapidoth Information Systems Laboratory University of Stanford Stanford CA USA

A source sequence is described by the index of the codeword in some codebook C that is closest to it according to the distortion measure d/sub 0/(x,x/spl circ//sub 1/). We study the distortion associated with reconstructing the source sequence so as to minimize the distortion measured by d/sub 1/(x,x/spl circ//sub 1/), which is in general different from d/sub 0/(x,x/spl circ//sub 0/). Using a random coding argument we derive an upper bound on the resulting distortion. Applying this bound to blocks of source symbols we construct a sequence of bounds which are shown to converge to the least distortion achievable in this setup. This solves the rate distortion dual of an open problem related to the mismatched capacity of channels. Addressing a different kind of mismatch, we also study mean-squared-error description of non-Gaussian sources with Gaussian codebooks. It is shown that the use of a Gaussian codebook to compress any ergodic source results in an average distortion which depends on the source only via its second moment. The hardest source to describe is the memoryless Gaussian source, and it is best described using a Gaussian codebook. Once a Gaussian codebook is used, we show that all sources of a given second moment become equally hard to describe.

关键词： Encoding Distortion measurement Information systems Laboratories Upper bound Rate-distortion Gaussian processes Decoding compression algorithms Block codes

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Multispectral image compression algorithms

Multispectral image compression algorithms

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Data compression Conference (DCC)

作者： T. Markas J. Reif Center for Systems Engineering Research and Triangle Institute NC USA Department of Electrical Enginnering Duke University Durham NC USA Department of Computer Science Duke University Durham NC USA

This paper presents a data compression algorithm capable of significantly reducing the amounts of information contained in multispectral and hyperspectral images. The loss of information ranges from a perceptually lossless level, achieved at 20-30:1 compression ratios, to a one where exploitation of the images is still possible (over 100:1 ratios). A one-dimensional transform coder removes the spectral redundancy, and a two-dimensional wavelet transform removes the spatial redundancy of multispectral images. The transformed images are subsequently divided into active regions that contain significant wavelet coefficients. Each active block is then hierarchically encoded using multidimensional bitmap trees. Application of reversible histogram equalization methods on the spectral bands can significantly increase the compression/distortion performance. Landsat Thematic Mapper data are used to illustrate the performance of the proposed algorithm.< >

关键词： Multispectral imaging compression algorithms Image coding Wavelet transforms Data compression Hyperspectral imaging Wavelet coefficients Multidimensional systems Histograms Satellites

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Lossless compression algorithms for High Fidelity Audio compression

Lossless Compression Algorithms for High Fidelity Audio Comp...

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IEEE International Symposium on Information Theory

作者： T. Shamoon C. Heegard School of Electrical Engineering Cornell University Ithaca NY USA

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A speech coding algorithm based on predictive coding

A speech coding algorithm based on predictive coding

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Data compression Conference (DCC)

作者： S. Kwong K.F. Man Department of Computer Science City University of Hong Kong Hong Kong China

Summary form only given. A compression algorithm for high quality speech signal using predictive coding techniques is developed. Code-excited linear predictive coding (CELPC) is one of the key techniques to compress speech signal to a bit-rate around 4.8 Kbps. However, due to the heavy computational requirement in the CELPC and speech signals usually can be divided into two portions: namely the based-band and the high-band frequency range. A hybrid CELPC and voice excited linear predictive coding (VELPC) scheme is developed for speech coding to reduce the complexity of the original CELPC. In the algorithm, a speech signal is firstly divided into two portions, the based-band and high-band respectively, in frequency domain, and then the low portion is coded with CELPC and the high-band portion is coded with VELPC. The test experiments showed this new coder can produce synthesized speech with good quality at a better bit rates than the original CELPC. When using the coding methods for the base-band and the high-band signal, we must decide how to divide the speech signal into two portions. In choosing the bandwidth of the base-band signal, there is a trade-off between the coding quality and the bit rate. In our experiment, the bandwidth of the base-band signal is chosen as one fourth of that of the original speech. Subjective evaluation experiments were conducted to test the performance of the hybrid CELPC and VELPC technique. For speech signal sampled at 8 kHz, a bit rate of 4.0 kbps can be achieved with frame intervals of 23 ms. The experimental results showed that the quality of the synthesized speech using hybrid coding technique at the bit rate of 4.0 kbps was almost the same as that of the CELPC at the bit rate of 4.8 kbps.

关键词： Speech coding Prediction algorithms Predictive coding Bit rate Speech synthesis Linear predictive coding Testing Signal synthesis Bandwidth compression algorithms

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Text segmentation using linear transforms

Text segmentation using linear transforms

引用

Asilomar Conference on Signals, Systems & Computers

作者： N. Chaddha A. Gupta Computer Systems Laboratory University of Stanford Stanford CA USA

Block-based linear transforms have found widespread use in image and video compression. However popular compression algorithms using such transforms, such as JPEG, which are very effective in compressing continuous tone images, do not perform well on mixed-mode images which have a substantial text component. With a growing number of applications where such images occur, e.g., color facsimile, digital libraries and educational videos, there are advantages in being able to classify each block as being text or continuous tone. With such a classification, different compression parameters or even algorithms may be employed for the two kinds of data to obtain high compression with minimal loss in visual quality. In this paper we propose algorithms for text segmentation based on a variety of linear transforms. We analyze the algorithms based on the accuracy and robustness of segmentation. Our results show that any of the popular linear transforms (DCT, DHT, DFT, WHT, DWT) can be used for accurate and robust text segmentation. An important practical implication of our results is that system designers can now use the same transform for both segmentation and compression, thus obtaining substantial savings in computational cost while improving quality.

关键词： Image coding Video compression Robustness Image segmentation compression algorithms Transform coding Facsimile Software libraries Algorithm design and analysis Discrete cosine transforms

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Progress towards a new government standard 2400 bps voice coder

Progress towards a new government standard 2400 bps voice co...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： M.A. Kohler L.M. Supplee T.E. Tremain U.S. Department of Defense Fort Meade MD USA

In order to support the need for higher quality low rate voice communications for government, industry, and military customers, the United States Government is conducting a search for a new voice compression algorithm at 2400 bits per second (bps). The United States Department of Defense Digital Voice Processing Consortium (DDVPC), consisting of members from civilian and military branches of the US Government, is directing the testing and evaluation of several candidate 2400 bps algorithms. The goal of the DDVPC is to select a new algorithm which meets or exceeds the published requirements by mid 1996. The selected algorithm, to become the new standard, should be implementable in a small, low powered device by 1997. This paper describes the status of the testing and evaluation process from its beginning in early 1993 through the end of 1994.

关键词： Code standards US Government Acoustic testing compression algorithms Background noise Working environment noise Communication standards Delay Speech enhancement Speech processing

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