The developments in wavelet theory have given rise to the wavelet thresholding method, for extracting a signal from noisy data [1,2]. Multiwavelets, wavelets with several scaling functions, have recently been introduc...
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ISBN:
(纸本)0780376226
The developments in wavelet theory have given rise to the wavelet thresholding method, for extracting a signal from noisy data [1,2]. Multiwavelets, wavelets with several scaling functions, have recently been introduced and they offer simultaneous orthogonality, symmetry and short support;which is not possible with ordinary wavelets, also called scalar wavelets [3]. This property makes multiwavelets more suitable for various signalprocessingapplications, especially compression and denoising. Like scalar wavelets, multiwavelets can be realized as filterbanks, however the filterbanks are now matrix-valued;requiring two or more input streams, which can be accomplished by prefiltering. In this paper, several thresholding methods to be used with different multiwavelets for image denoising are presented. The performances of multiwavelets are compared with those of scalar wavelets. Simulations reveal that multiwavelet based image denoising schemes outperform wavelet based methods both subjectively and objectively.
EMG signals can be considered as the sum of scaled and delayed versions of a single prototype. We have applied the wavelet Transform choosing the mother wavelet so as to match the known shape of the basic component, a...
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ISBN:
(纸本)0819425915
EMG signals can be considered as the sum of scaled and delayed versions of a single prototype. We have applied the wavelet Transform choosing the mother wavelet so as to match the known shape of the basic component, and have compared the results obtained with different wavelets. The results in terms of MUAP detection and resolution are very encouraging even in the presence of asymmetric shape and high levels of additive noise.
Integration of the nonlinear approaches for system identification is proposed for spectral differentiation and object recognition in this research. Multi-scale nonlinear principal component analysis (NCA) has been imp...
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ISBN:
(纸本)9781424446018
Integration of the nonlinear approaches for system identification is proposed for spectral differentiation and object recognition in this research. Multi-scale nonlinear principal component analysis (NCA) has been implemented to analyze the individual components of approximations and details based on wavelet transform. Neural network training has been applied to NCA while both ID and 2D wavelet transform have been conducted across different scales. At each scale, the principal components are selected in order to reconstruct the intrinsic signal and image. This statistical identification approach is essential to enhance multivariate data processing. Case studies on signal and imageprocessing are both conducted. In addition, quantitative measures are presented to analyze the nonlinear multi-scale approach from the objective perspectives.
Recently, a logarithmic imageprocessing model called Symmetric Logarithmic imageprocessing (S-LIP) has been investigated in the framework of the multiresolution analysis (MRA) performed by wavelet transform. The S-L...
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ISBN:
(纸本)9781479983391
Recently, a logarithmic imageprocessing model called Symmetric Logarithmic imageprocessing (S-LIP) has been investigated in the framework of the multiresolution analysis (MRA) performed by wavelet transform. The S-LIP model is an extension of the Logarithmic imageprocessing (LIP) model. The motivation of this work is to implement classical waveletapplications in the S-LIP framework. The underlying idea is to take advantage of both the multiscale analysis performed by the wavelet transform and the logarithmic processing of the pixels' intensity by the S-LIP model. The S-LIP wavelet transform is introduced and applied to automatic denoising in order to highlight its intrinsic characteristics. As an illustration, signal-to-Noise Ratios for both the linear wavelet transform and S-LIP wavelet transform are calculated for different levels of Gaussian, Poisson, Speckle and salt-and-pepper noises.
waveletsignalprocessing has demonstrated remarkable capabilities in reducing noise, achieving better resolution through edge detection and increasing data transmission by means of data compression. While wavelets ar...
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ISBN:
(纸本)0819441929
waveletsignalprocessing has demonstrated remarkable capabilities in reducing noise, achieving better resolution through edge detection and increasing data transmission by means of data compression. While wavelets are digital, another field, Optical Phase Conjugation (OPC), is analog and has been applied to similar problems: signal and image distortion reduction and optical data storage. wavelets have been applied to optical solitons, laser beam diagnostics, diode laser arrays, interferometry and optical correlators. waveletsignalprocessing will be applied to Optical Phase Conjugation to examine laser beam interaction in nonlinear crystals and remove distortion from input and output laser beams.
New wavelet techniques are designed to improve the perceptual quality of images/signal, enhance and detect the detail features in the region of interest (ROI). Distributed approximating functionals (DAFs) are used to ...
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ISBN:
(纸本)0780362934
New wavelet techniques are designed to improve the perceptual quality of images/signal, enhance and detect the detail features in the region of interest (ROI). Distributed approximating functionals (DAFs) are used to construct a new class of smooth wavelets, which enable better signalprocessing performance. This paper is focused on recent improvements in DAF waveletsignalprocessing. The combined perceptual techniques (such as regularization, visual group normalization and contrast nonlinear enhancement) produce natural high-quality images based on the human vision system. The underlying technologies significantly facilitate the creation of generic signalprocessing and computer-aided diagnostic (CAD) systems.
This paper addresses the image denoising problem using a newly proposed digital image transform: the finite ridgelet transform (FRIT). The transform is invertible, non-redundant and achieved via fast algorithms. Furth...
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ISBN:
(纸本)0819437646
This paper addresses the image denoising problem using a newly proposed digital image transform: the finite ridgelet transform (FRIT). The transform is invertible, non-redundant and achieved via fast algorithms. Furthermore this transform can be designed to be orthonormal thus indicating its potential in many other imageprocessingapplications. We then propose various improvements on the initial design of the FRIT in order to make it to have better energy compaction and to reduce the border effect. Experimental results show that the new transform outperforms wavelets in denoising images with linear discontinuities.
In image watermarking, hybrid approaches increase imperceptibility and robustness. Also, a scaling factor is used, which should be optimized when combining the cover image and watermark. In this study, discrete wavele...
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ISBN:
(纸本)9781665450928
In image watermarking, hybrid approaches increase imperceptibility and robustness. Also, a scaling factor is used, which should be optimized when combining the cover image and watermark. In this study, discrete wavelet transform and discrete cosine transform (DCT) were used together. The watermark-edge image was obtained by randomly inserting the watermark on the horizontal, vertical and diagonal edge points of the cover image detected with Sobel. The DCT frequency components of the watermark-edge image were weighted with a generated matrix and combined with the DCT of the cover image. According to the obtained results, the proposed method is imperceptible and robust to various attacks, especially JPEG compression and noise attacks.
imageprocessing has gained an increased usage and impact in modern pavement networks automatic distress severity classification (DSC). DSC defines priorities and maintenance resources optimum allocation in order to a...
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ISBN:
(纸本)9781728133775
imageprocessing has gained an increased usage and impact in modern pavement networks automatic distress severity classification (DSC). DSC defines priorities and maintenance resources optimum allocation in order to achieve a cost-effective rehabilitation process. This paper presents a novel computer vision algorithm having the ability to process, isolate and evaluate the distress severity level of a pavement. A pavement color image is converted to grayscale and then processed for image denoising of the granularity and complex texture that represent and artifact in cracks edge detection. The processing is achieved by a 2D dual-tree double density wavelet transform filter banks that significantly reduces the granularity noise while preserving the pavement cracks for edge detection. The 2D wavelet FIR filters perform analysis, soft thresholding then a synthesis of the image. The second step is then an edge detection process followed by morphological filtering and labeled components size-histogram filter to isolate false edges as residuals of denoising. A final step is performed by two Savitzky-Golay filters for the detection of longitudinal and transverse alligator cracks projections. A weighted score function with multiple parameters is used for DSC.
Lifting scheme for the real field wavelet transform has provided a new insight into its practical implementation. This paper shows that a similar scheme can be developed for the binary field wavelet transform. In part...
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ISBN:
(纸本)0780367251
Lifting scheme for the real field wavelet transform has provided a new insight into its practical implementation. This paper shows that a similar scheme can be developed for the binary field wavelet transform. In particular, by using the Euclidean algorithm the binary filters can be decomposed into a finite sequence of simple lifting steps over the binary field. This provides an alternative method for the implementations of the binary field wavelet transform for imageprocessingapplications. It is found that the new implementation can reduce the number of arithmetic operations involved in the transform and allow an efficient in-place implementation structure.
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