We develop a new algorithm for multirate filter bank optimization, which finds application in subband coding or waveletsignal analysis. Although some impressive off-line algorithms have recently been developed for th...
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We develop a new algorithm for multirate filter bank optimization, which finds application in subband coding or waveletsignal analysis. Although some impressive off-line algorithms have recently been developed for this purpose, the computation demand of such algorithms often renders them prohibitive for real-time applications. In this vein, adaptive filtering solutions remain of interest. A simple gradient descent algorithm may be ill suited due to the nonquadratic nature of the cost function to be minimized, and accordingly non gradient algorithms may offer some attractive alternatives. The present paper describes a projection type algorithm, which aims to construct a lossless filter bank such that one of its impulse responses lies close to an extremal eigenvector of the input signal autocorrelation matrix. Though a formal convergence proof of the algorithm is not offered, simulations show that the algorithm converges to an acceptable vicinity of the global minimum point of the cost function.
Data compression is dominated by the Fourier or wavelet transforms which approximate the given function or sequence as a linear sum of the basis functions. In this paper, we discuss the use of dynamical systems for co...
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ISBN:
(纸本)0780336798
Data compression is dominated by the Fourier or wavelet transforms which approximate the given function or sequence as a linear sum of the basis functions. In this paper, we discuss the use of dynamical systems for compression. Since leaky-integrator model neural nets can approximate arbitrary finite sequences, we propose to compress a 'not too wild' signal by a recurrent neural network. As an initial valued problem, the information to be stored are the parameters of the system and the initial states. Elementary analysis on error and compression ratio are also given.
signal decomposition techniques are an important tool for analyzing nonstationary signals. The proper selection of time-frequency basis functions for the decomposition is essential to a variety of signalprocessing ap...
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ISBN:
(纸本)0819418447
signal decomposition techniques are an important tool for analyzing nonstationary signals. The proper selection of time-frequency basis functions for the decomposition is essential to a variety of signalprocessingapplications. The discrete wavelet transform (DWT) is increasingly being used for signal analysis, but not until recently has attention been paid to the time-frequency resolution property of wavelets. This paper describes additional results on our procedure to design wavelets with better time-frequency resolution. In particular, our optimal duration-bandwidth product wavelets (ODBW) have better duration-bandwidth product, as a function of wavelet-defining filter length N, than Daubechies' minimum phase and least- asymmetric wavelets, and Dorize and Villemoes' optimum wavelets over the range N equals 8 to 64. Some examples and comparisons with these traditional wavelets are presented.
We propose an improved statistical characterization of the field of wavelet coefficients of natural images. Based on this characterization, we introduce Morphological Representation of wavelet Data (MRWD), a novel cod...
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ISBN:
(纸本)0780324323
We propose an improved statistical characterization of the field of wavelet coefficients of natural images. Based on this characterization, we introduce Morphological Representation of wavelet Data (MRWD), a novel coding framework for both image and video coding applications. MRWD departs from existing wavelet-based coders in its use of a radically different set of primitive operations -non-linear, morphological operations-, for efficiently encoding the wavelet data field. Simulation results are very encouraging: a preliminary algorithm based on the morphological data structure is able to achieve about 0.5 dB of gain in SNR over Shapiro's state-of-the-art zerotree-based wavelet coder [1] at a coding rate of 1 bpp for the 'Lenna' image.
This wavelet based data compression algorithm addresses a growing need to handle large quantities of image data quickly and efficiently. This wavelet technique has been coded based on the assumption that small coeffic...
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ISBN:
(纸本)0819418447
This wavelet based data compression algorithm addresses a growing need to handle large quantities of image data quickly and efficiently. This wavelet technique has been coded based on the assumption that small coefficients computed by the two-dimensional orthogonal wavelet transform are principally associated with image noise, and only the largest values are required to capture the information content of the respective source image. The approach has been successfully applied to one-dimensional signals in the design of signal classifiers. This particular algorithm for wavelet-based image compression has been designed and compared to the Joint Photographic Expert Group (JPEG) still picture image compression standard. Examples are shown of side scan sonar images, x rays, and laser line scan images.
wavelet based compression schemes belong to the general class of transform coding schemes. We show how the genetic programming approach can be used to optimize such a compression scheme in the sense of rate-distortion...
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ISBN:
(纸本)0819419281
wavelet based compression schemes belong to the general class of transform coding schemes. We show how the genetic programming approach can be used to optimize such a compression scheme in the sense of rate-distortion. The results of optimized wavelet based compression scheme are compared with the JPEG compression standard. A prototype implementation of the method is realized as a distributed, parallel implementation on a heterogeneous Unix network.
We present a highly powerful, modular, and interactive software tool for the analysis of timefrequency coherent signals via wavelet transformations. A major design goal of the waveletsignalprocessing Workstation (WS...
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Mathematical morphology, as originally described by Matheron and Serra, consists of the application of set theoretical operations between the image set X and a structure element set B. image skeletons are very efficie...
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ISBN:
(纸本)0819418447
Mathematical morphology, as originally described by Matheron and Serra, consists of the application of set theoretical operations between the image set X and a structure element set B. image skeletons are very efficient representations of shape, and can be directly derived using the morphological operations of erode and open. If done at full image resolution, derivation of a skeleton can be very time consuming without dedicated signalprocessing hardware. This paper presents an alternative to the standard approach that relies on morphological operations within the wavelet coefficient space. In particular, the skeleton transformation can be done very efficiently at the reduced resolution of the coarse wavelet coefficient levels. We investigate the relationship between waveletimage compression and morphological transforms for the derivation of skeletons. We also report the results of some experimental studies on binary and gray scale images.
In this paper, continuous-time wavelet transform (CTFT) is applied to analyze non- bandlimited continuous-time signals. Orthogonal CTWT based on Daubechies finite-support wavelets is used for signal analysis and recon...
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ISBN:
(纸本)0819418447
In this paper, continuous-time wavelet transform (CTFT) is applied to analyze non- bandlimited continuous-time signals. Orthogonal CTWT based on Daubechies finite-support wavelets is used for signal analysis and reconstruction. A procedure to compute CTWT coefficients for a given scale and translation is described. Both noise-free and noisy signals are used in the specific examples that we consider here.
A wavelet preprocessed amplitude-modulated phase-only filter has been implemented. It is evaluated in terms of various pattern recognition performance statistics. The effect of thresholding nonlinearity has also been ...
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ISBN:
(纸本)0819418447
A wavelet preprocessed amplitude-modulated phase-only filter has been implemented. It is evaluated in terms of various pattern recognition performance statistics. The effect of thresholding nonlinearity has also been studied.
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