image enhancement and restoration methods are essential for many fields like medical imaging and radar imaging systems. In literature, there are many studies and different approaches to image enhancement and restorati...
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ISBN:
(纸本)9781467355636;9781467355629
image enhancement and restoration methods are essential for many fields like medical imaging and radar imaging systems. In literature, there are many studies and different approaches to image enhancement and restoration methods. In this paper, some noise models are studied and the performances of Wiener filter, median filter, mean filter and a proposed method based on adaptive wavelet thresholding are compared on images degraded by mentioned noise models.
This paper presents a new method for light field applications such as content replacement and fusion in the gradient domain. This approach is inspired by successful gradient domain based image and video editing techni...
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This paper presents a new method for light field applications such as content replacement and fusion in the gradient domain. This approach is inspired by successful gradient domain based image and video editing techniques. A necessary and important part of gradient-based solutions is recovering the signal of interest from artificially generated, and typically non-integrable, gradient data. As such, a new algorithm is developed to reconstruct a light field from a given gradient data set. In the algorithm, first, the 4D Haar wavelet decomposition of the light field is obtained from the given gradient data. Then, the light field is obtained from a wavelet synthesis step. This algorithm is intended as a building block for gradient-based light field editing methods, and as such, its performance is analysed on a set of benchmark light field data sets. The proposed reconstruction algorithm is an essential part in developing solutions for two light field problems: light field editing and light field fusion. Results show that processing light fields in the gradient domain offers significant advantages over processing in the intensity domain.
This paper aims at reviewing the recent published works dealing with industrial applications of wavelet and, more generally speaking, multiresolution analysis. After a quick recall in a simple overview of the basics o...
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ISBN:
(纸本)0819455601
This paper aims at reviewing the recent published works dealing with industrial applications of wavelet and, more generally speaking, multiresolution analysis. After a quick recall in a simple overview of the basics of wavelet transform and of its main variations, some of its applications are reviewed domain by domain, beginning with signalprocessing, continuous and discrete wavelet transform proceeding with imageprocessing and applications. More than 150 recent papers are presented in these two sections.
The use of space-scale representations for the frequential analysis of oriented textures is investigated For this purpose, the Continuous wavelet Transform (CWT) is considered. Its discretisation in the framework of t...
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ISBN:
(纸本)0819425915
The use of space-scale representations for the frequential analysis of oriented textures is investigated For this purpose, the Continuous wavelet Transform (CWT) is considered. Its discretisation in the framework of the Mellin-Transform is described. The behavior of this transformation as a tool for space-frequency representation is compared to the Wigner Distribution on test images. Parameters measuring shape and orientation of local spectra are extracted from these representations, and illustrated on natural textures.
Integer based-matrix algorithms for discrete Haar transform (DHT) and discrete wavelet transform (DWT) are proposed with relation to the multiresolution representation (MRR). A recursive wavelet transform technique is...
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ISBN:
(纸本)0819425915
Integer based-matrix algorithms for discrete Haar transform (DHT) and discrete wavelet transform (DWT) are proposed with relation to the multiresolution representation (MRR). A recursive wavelet transform technique is used with a view to demonstrating simply lossy reconstructed images in contrast to an original image under the specified resolution size. A visual effect of reconstructed images with differnt appearance and image quality, caused by modifying or throwing away a part of the 2-D HT or WT coefficients, is discussed with a measure of quantitative evaluation such as similarity and/or modified similarity, and fidelity RMSE and/or PSNR.
wavelet shrinkage is a signal estimation technique that exploits the remarkable abilities of the wavelet transform for signal compression. wavelet shrinkage using thresholding is asymptotically optimal in a minimax me...
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ISBN:
(纸本)0819425915
wavelet shrinkage is a signal estimation technique that exploits the remarkable abilities of the wavelet transform for signal compression. wavelet shrinkage using thresholding is asymptotically optimal in a minimax mean-square error (MSE) sense over a variety of smoothness spaces. However, for any given signal, the MSE-optimal processing is achieved by the Wiener filter, which delivers substantially improved performance. In this paper, we develop a new algorithm for wavelet denoising that uses a wavelet shrinkage estimate as a means to design a wavelet-domain Wiener filter. The shrinkage estimate indirectly yields an estimate of the signal subspace that is leveraged into the design of the filter. A peculiar aspect of the algorithm is its use of two wavelet bases: one for the design of the empirical Wiener filter and one for its application. Simulation results show up to a factor of 2 improvement in MSE over wavelet shrinkage, with a corresponding improvement in visual quality of the estimate. Simulations also yield a remarkable observation: whereas shrinkage estimates typically improve performance by trading bias for variance or vice versa, the proposed scheme typically decreases both bias and variance compared to wavelet shrinkage.
In this work a new way to improve the representation of images using a discrete wavelet transform for coding purposes is presented. The idea lies in combining all wavelet coefficients related to detail information at ...
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ISBN:
(纸本)0818679204
In this work a new way to improve the representation of images using a discrete wavelet transform for coding purposes is presented. The idea lies in combining all wavelet coefficients related to detail information at a same resolution level but along different orientations (horizontal, vertical, and diagonal), into a single image. Given that detail information is located for all subband images in the neighborhood of high frequency textures or edge locations, the pattern of significant coefficients remains unchanged after the combination process. This process allows further to reduce the number of transformed coefficients by 2/3, while preserving the multiresolution structure. This information can thus be efficiently coded using a multiresolution embedded coding scheme, such as Shapiro's zerotree coder. Overall, a higher coding efficiency can be reached while preserving the cross-scale prediction of significance among coefficients. Ultimately, approximate detail information must be recovered from the combined and coded data for each subband of the original wavelet, so as to reconstruct a decoded image.
The denoising of a natural image corrupted by Gaussian noise is a classical problem in signal or imageprocessing. Donoho and his coworkers at Stanford pioneered a wavelet denoising scheme by thresholding the wavelet ...
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The denoising of a natural image corrupted by Gaussian noise is a classical problem in signal or imageprocessing. Donoho and his coworkers at Stanford pioneered a wavelet denoising scheme by thresholding the wavelet coefficients arising from the standard discrete wavelet transform. This work has been widely used in science and engineering applications. However, this denoising scheme tends to kill too many wavelet coefficients that might contain useful image information. In this paper, we propose one waveletimage thresholding scheme by incorporating neighbouring coefficients, namely NeighShrink. This approach is valid because a large wavelet coefficient will probably have large wavelet coefficients as its neighbours. Experimental results show that NeighShrink is better than the Wiener filter and the conventional wavelet denoising approaches: visuShrink and SUREShrink. We also investigate different neighbourhood sizes and find that a size of 3 x 3 is the best among all window sizes.
Dual tree complex wavelet transform (DT-CWT) has the advantages of nearly shift-invariance and directional selectivity (for two or more dimensions) over the classical discrete wavelet transform. These advantages are e...
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ISBN:
(纸本)9781467373869
Dual tree complex wavelet transform (DT-CWT) has the advantages of nearly shift-invariance and directional selectivity (for two or more dimensions) over the classical discrete wavelet transform. These advantages are essential for many signalprocessingapplications (i.e. image fusion, image enhancement, pattern recognition). In his study, a speech enhancement method based on the DT-CWT has been proposed in order to test its performance in speech enhancement. An efficient estimator, multiplicatively modified log-spectral amplitude (MM-LSA) estimator is used for the enhancement of noisy subband wavelet coefficients. The objective and experimental results show the superiority of the proposed method to the wavelet transform based methods well known in the literature.
A complete wavelet-based image storage and indexing system for progressive coding, indexing, retrieval. and transmission of images over the network is proposed in this research. New wavelet domain features which inclu...
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ISBN:
(纸本)0819425915
A complete wavelet-based image storage and indexing system for progressive coding, indexing, retrieval. and transmission of images over the network is proposed in this research. New wavelet domain features which include subband significance, decomposition structure. luminance and chrominance histograms, and the significance map of the lowest frequency channel are used to achieve content-based indexing and retrieval. The proposed indexing features take into account of the color: brightness, texture, frequency, and spatial information of a given query image. All features can be naturally extracted as a byproduct during the image compression stage with wavelets. Since coding and indexing are integrated in an unified framework in the proposed system, the database management is greatly simplified. Extensive experimental results are given to demonstrate the retrieval performance of the new approach.
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