An LMS adaptive filtering algorithm is presented utilizing wavelet transforms. Its performance is compared to DCT and Walsh-Hadamard transform-based adaptive filtering. The experimental analysis is performed in the ca...
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ISBN:
(纸本)0819416274;9780819416278
An LMS adaptive filtering algorithm is presented utilizing wavelet transforms. Its performance is compared to DCT and Walsh-Hadamard transform-based adaptive filtering. The experimental analysis is performed in the case of the system identification of an unknown system or filter for stationary input signals. The results show some improvement in the weight modelling of the filter with comparable convergence rates. A new performance criteria, the diagonality factor, is introduced in order to show the specific effect of the wavelet transform on a signal. A Mean Average Difference is also utilized to compare the weight modelling performance of the various transform-based LMS adaptive filterings studied in this paper.
In this paper, a wavelet packet transform wideband beamforming (WPTWB) is proposed. The proposed method employs wavelet packet analysis and synthesis filter banks, replacing the traditional analysis and synthesis filt...
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ISBN:
(纸本)9798350350920
In this paper, a wavelet packet transform wideband beamforming (WPTWB) is proposed. The proposed method employs wavelet packet analysis and synthesis filter banks, replacing the traditional analysis and synthesis filter banks used in subband beamforming, to achieve the decomposition and reconstruction of wideband signals. And the algorithm leverages the inherent multiresolution characteristics of the wavelet packet transform to capture both the nuanced details and broader generalizations present in broadband signals. Simulation experiments demonstrate the anti-interference ability and accuracy of the algorithm.
This paper introduces the problem of designing quincunx lifting scheme well-adapted to lossy compression applications. The main goal is to design quincunx filters adapted to the statistical properties of input signal ...
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ISBN:
(纸本)0780367251
This paper introduces the problem of designing quincunx lifting scheme well-adapted to lossy compression applications. The main goal is to design quincunx filters adapted to the statistical properties of input signal in order to perform a better signal reconstruction after deterioration due to a lossy coding. To perform such a filtering, the basic idea is to combine optimization methods and lifting scheme. The latter is an attractive tool to perform wavelet tranforms.
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.
Our goal in this article is to present a quantitative study about speech recognition and the inherent problems of its applications and the computer processing. Our approach is characterized by independent speaker and ...
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ISBN:
(纸本)0819425915
Our goal in this article is to present a quantitative study about speech recognition and the inherent problems of its applications and the computer processing. Our approach is characterized by independent speaker and we made use of pre-processing the concept as wavelets Transform and as pattern recognition an Artificial Neural Network (ANN - Multilayer Perceptron -Backpropagation Algorithm).
We propose a new image compression scheme based on fractal coding of a wavelet transform coefficients using a fast non-iterative algorithm for the codebook generation. The original image is first decomposed into subba...
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ISBN:
(纸本)0818679204
We propose a new image compression scheme based on fractal coding of a wavelet transform coefficients using a fast non-iterative algorithm for the codebook generation. The original image is first decomposed into subbands containing information indifferent spatial directions and different scales, using an orthogonal wavelet filter bank. Subbands are encoded using local Iterated Function Systems (LIFS) with range and domain blocks presenting horizontal or vertical directionalities. Their sizes are estimated according to the correlation lengths and resolution of each subband. The computational complexity is greatly decreased by using subband decomposition. In addition a fast non-iterative algorithm is implemented for the blocks classification. This algorithm creates progressively the codebook during only one scanning of the training set. We proves the efficiency of the proposed approach both in terms of PSNR/bit rate and computation time.
This paper develops algorithms for calculating commonly used energy measures directly from the data stream of wavelet-compressed images. Incorporating these techniques into an underlying computational kernel allows ma...
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This paper develops algorithms for calculating commonly used energy measures directly from the data stream of wavelet-compressed images. Incorporating these techniques into an underlying computational kernel allows many image-processing tasks to be efficiently implemented in the compressed domain. Compared to traditional decompress-process methods, the proposed techniques offer significant memory savings and reduce the computational load of the system. Experimental results show that the calculated energy values are accurate and obtained with less strain on system resources. The potential savings achieved by incorporating the proposed kernel are illustrated in a texture classification example.
In this paper, we propose using Partial Differential Equation (PDE) techniques in wavelet based imageprocessing to reduce edge artifacts generated by wavelet thresholding. We employ minimization techniques, in partic...
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ISBN:
(纸本)0780362985
In this paper, we propose using Partial Differential Equation (PDE) techniques in wavelet based imageprocessing to reduce edge artifacts generated by wavelet thresholding. We employ minimization techniques, in particular the minimization of total variation (TV), to modify the retained standard wavelet coefficients so that the reconstructed images have less oscillations near edges. Numerical experiments show that this approach improves the reconstructed image quality in wavelet compression and in denoising.
The discrete wavelet transform (DWT) gives a compact multiscale representation of signals and provides a hierarchical structure for signalprocessing. It has been assumed the DWT can fairly well decorrelate real-world...
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ISBN:
(纸本)0780362934
The discrete wavelet transform (DWT) gives a compact multiscale representation of signals and provides a hierarchical structure for signalprocessing. It has been assumed the DWT can fairly well decorrelate real-world signals. However a residual dependency structure still remains between wavelet coefficients. It. has been observed magnitudes of wavelet coefficients are highly correlated, both across the scale and at neighboring spatial locations. In this paper we present, a wavelet folding technique, which folds wavelet coefficients across the scale and removes the across-the-scale dependence to a larger extent. It produces an even more compact signal representation and the energy is more concentrated in a few large, coefficients. It has a great potential in applications such as image compression.
作者：
Lu, JApple Computer
Compression and Signal Processing Dept. MS 302-3MT Cupertino CA 95014 2 Infinite Loop United States
This paper studies the algorithms that reconstruct a signal from its wavelet extrema representation. We show that the existing reconstruction algorithms are inadequate in assuring a consistent reconstruction. We furth...
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ISBN:
(纸本)0819425915
This paper studies the algorithms that reconstruct a signal from its wavelet extrema representation. We show that the existing reconstruction algorithms are inadequate in assuring a consistent reconstruction. We further propose a method that can be used with a number of existing algorithms to guarantee a consistent reconstruction. The new method provides a rigorous way to prevent artifacts resulting from the spurious wavelet extrema in the reconstructed signal.
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