In this paper we aim at providing a robust and more compact approach for detecting edges compared to the traditional edge detection algorithms like Roberts, Sobel, Prewitt and evolutionary-inspired Ant Colony Optimiza...
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ISBN:
(纸本)9781467373869
In this paper we aim at providing a robust and more compact approach for detecting edges compared to the traditional edge detection algorithms like Roberts, Sobel, Prewitt and evolutionary-inspired Ant Colony Optimization (ACO) techniques. In this proposed approach, an ACO is used alongside Dual-Tree Complex wavelet Transform (DT-CWT) to detect and emphasize edges that would have been difficult to obtain with directly applying ACO or conventional edge detection algorithms. Initially the image is decomposed using DT-CWT to obtain the oriented wavelets and approximation versions of the original image. ACO is applied to each of the decomposed images and then image is reconstructed to get the processed image with the detected edges. The results obtained reveal superior, more detailed and emphasized edges than directly applying ACO or other conventional techniques. The proposed approach is also capable of identifying edges in slightly varying intensity regions.
wavelet threshold algorithms replace wavelet coefficients with small magnitude by zero and keep or shrink the other coefficients. This is basically a local procedure, since wavelet coefficients characterize the local ...
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ISBN:
(纸本)0819432997
wavelet threshold algorithms replace wavelet coefficients with small magnitude by zero and keep or shrink the other coefficients. This is basically a local procedure, since wavelet coefficients characterize the local regularity of a function. Although a wavelet transform has decorrelating properties, structures in images, like edges, are never decorrelated completely, and these structures appear in the wavelet coefficients. We therefore introduce a geometrical prior model for configurations of large wavelet coefficients and combine this with the local characterization da classical threshold procedure into a Bayesian framework. The threshold procedure selects the large coefficients in the actual image. This observed configuration enters the prior model, which, Pry itself, only describes configurations, not coefficient values. In this way, we can compute for each coefficient the probability of being "sufficiently clean".
In this work, we consider the problem of blind source separation in the wavelet domain via a Bayesian estimation framework. We use the sparsity and multiresolution properties of the wavelet coefficients to model their...
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ISBN:
(纸本)0819450804
In this work, we consider the problem of blind source separation in the wavelet domain via a Bayesian estimation framework. We use the sparsity and multiresolution properties of the wavelet coefficients to model their distribution by heavy tailed prior probability laws: the generalized exponential family and the Gaussian mixture family. Appropriate MCMC algorithms are developped in each case for the estimation purposes and simulation results are presented for comparison.
wavelet domain image resolution enhancement algorithms assume that the available image is the low-frequency subband of a higher resolution image and high-frequency subbands are not available. Then, these high-frequenc...
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ISBN:
(纸本)9781424407194
wavelet domain image resolution enhancement algorithms assume that the available image is the low-frequency subband of a higher resolution image and high-frequency subbands are not available. Then, these high-frequency coefficients are estimated and the higher resolution image is generated by application of inverse wavelet transform. Some of these techniques have used probabilistic methods and utilisation of HMT (Hidden Markov Tree) was shown to produce promising results. HMT based methods model the wavelet coefficients as Gaussian distributions. However, as Gaussian distributions are symetrical around zero, coefficient signs are generated randomly and have an equal change of being positive or negative. In this paper, significance of having correst coefficient sign information is demonstrated and a post-processing method is proposed to increase the accuracy of the estimated signs.
High-resolution optical mapping is an emerging technique to record the activation and propagation of transmembrane potential on the surface of cardiac tissues. Important electrodynamic information previously not avail...
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ISBN:
(纸本)0819429139
High-resolution optical mapping is an emerging technique to record the activation and propagation of transmembrane potential on the surface of cardiac tissues. Important electrodynamic information previously not available from extracellular electric recording could be extracted from these detailed optical recordings. The noise contamination in the images is a major obstacle that prohibits higher level of information extraction. Because the patterns of interest contain sharp wavefronts and structures that we wish to detect and track in a series of: flames, we seek to perform denoising based on wavelet decomposition approaches. Among the wavelet denoise methods that were tested in this preliminary study, the wavelet packet produced the best results that could be extended to denoise the entire image sequence for multi-dimensional information processing.
We present a novel method to extract subimages from a huge reference image by using integer-type lifting wavelet transforms. Our integer to integer lifting wavelet transform contains controllable free parameters in th...
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ISBN:
(纸本)0819437646
We present a novel method to extract subimages from a huge reference image by using integer-type lifting wavelet transforms. Our integer to integer lifting wavelet transform contains controllable free parameters in the lifting term, which is constructed based on an integer version of Haar wavelet transform. Such free parameters are trained following a vanishing criterion for low frequency components of query images. The trained parameters have characteristics of the query images. We apply a lifting wavelet transform with such parameters to a reference image and check whether they satisfy our vanishing criterion or not, to extract target subimages.
Within the multi-resolution analysis, the study of the image compression algorithm using the Haar wavelet has been performed. We have studied the dependence of the image quality on the compression ratio. Also, the var...
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ISBN:
(数字)9781510603349
ISBN:
(纸本)9781510603332;9781510603349
Within the multi-resolution analysis, the study of the image compression algorithm using the Haar wavelet has been performed. We have studied the dependence of the image quality on the compression ratio. Also, the variation of the compression level of the studied image has been obtained. It is shown that the compression ratio in the range of 8-10 is optimal for environmental monitoring. Under these conditions the compression level is in the range of 1.7 - 4.2, depending on the type of images. It is shown that the algorithm used is more convenient and has more advantages than Winrar. The Haar wavelet algorithm has improved the method of signal and imageprocessing.
We presents results obtained by different contrast enhancement methods applied to medical images. We take into account classical histogram specification, local and wavelet-based techniques and a novel approach for mul...
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ISBN:
(纸本)0818679204
We presents results obtained by different contrast enhancement methods applied to medical images. We take into account classical histogram specification, local and wavelet-based techniques and a novel approach for multiscale contrast enhancement. The latter, whose rationale grounds in theories of visual perception, exploits a local definition of the Fechner-Weber's contrast within the-context of a non-linear scale-space representation generated by anisotropic diffusion. Our experimental fields concerns a difficult kind of medical images, namely digital mammographic images.
A new approach to FPGA implementation of two-dimensional discrete wavelet transform is presented. This architecture allow high accurate and sampling rate DWT realization based on FIR filters of substantial length to b...
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ISBN:
(纸本)0819425915
A new approach to FPGA implementation of two-dimensional discrete wavelet transform is presented. This architecture allow high accurate and sampling rate DWT realization based on FIR filters of substantial length to be implemented on current generation FPGAs. The scheme is based on two parallel pipelined linear phase 17-tap FIR filters with common shift register, partial adders and look-up tables as coefficient multipliers with 4-stage pipelined architecture. The transform is realized in three stages controlled by the state machine, where temporary (L and H) and final subimages (LL, LH, HL, and HH) are created. High throughput (1050 MIPS) and external memory controller allow efficient concurrent cooperation with external processors.
Dual-tree wavelet transforms have recently gained popularity [1] since they provide low-redundancy directional analyses of images. In our recent work, dyadic real dual-tree decompositions have been extended to the M-b...
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ISBN:
(纸本)1424407281
Dual-tree wavelet transforms have recently gained popularity [1] since they provide low-redundancy directional analyses of images. In our recent work, dyadic real dual-tree decompositions have been extended to the M-band case, so adding much flexibility to this analysis tool. In this work, we propose to further extend this framework on two fronts by considering (i) biorthogonal and (ii) complex M-band dual-tree decompositions. Denoising results are finally provided to demonstrate the validity of the proposed design rules.
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