Topic
Multiresolution analysis
About: Multiresolution analysis is a research topic. Over the lifetime, 4032 publications have been published within this topic receiving 140743 citations. The topic is also known as: Multiresolution analysis, MRA.
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TL;DR: From computer simulation, the merits of the proposed wavelet transform scheme based on Meyer algorithm over the conventional approaches are verified, in terms of achieving better performance based on the subjective and objective analysis.
20 citations
Dissertation•
01 Jan 2002
20 citations
TL;DR: A stabilization of the two-step lifting construction of Sweldens for wavelet bases on irregular meshes on the interval yields biorthogonal bases in which the wavelets on both the primal and the dual side have a chosen number of vanishing moments and have local support.
Abstract: We propose a stabilization of the two-step lifting construction of Sweldens for wavelet bases on irregular meshes on the interval. The method yields biorthogonal bases in which the wavelets on both the primal and the dual side have a chosen number of vanishing moments and have local support. We combine it with a constrained local semiorthogonalization to obtain a stabilized variant.
Numerical results show that the wavelet bases are well-conditioned, having approximately the same condition numbers as wavelet bases obtained by global semiorthogonalization, while the average support is not much larger than in the unstabilized construction.
20 citations
27 Mar 2010
TL;DR: A new image edge detection method based on the contourlet transform is proposed that improves over wavelet-based techniques and Canny detector, and also works well for noisy images.
Abstract: Wavelet multiresolution analysis allows us to detect edges at different scales, also to obtain other important aspects of the extracted edges. However, due to the usual two-dimensional tensor product, wavelet transform is not optimal for representing images. The main problem in edge detection using wavelet transform is that it can only capture point-singularities, and the extracted edges are not continuous. In order to solve that problem, we propose a new image edge detection method based on the contourlet transform. The directional multiresolution representation Contourlet takes advantages of the intrinsic geometrical structure of images, and is appropriate for the analysis of the image edges. Using the modulus maxima detection, an image edge detection method based on contourlet transform is proposed. To suppress the image noise effect on edge detection, the scale multiplication in contourlet domain is also proposed. Through real images experiments, the proposed edge detection method's performance for the extracted edges is analyzed and compared with other two edge detection methods. The experiment result proves that the proposed edge detection method improves over wavelet-based techniques and Canny detector, and also works well for noisy images.
20 citations
TL;DR: A novel receiver system based on the multiresolution time-frequency feature extraction capabilities of wavelet analysis, coupled with the well recognized pattern recognition performance of artificial neural networks for mitigating the effects of bandwidth limiting channel-induced distortion is introduced.
Abstract: Optical wireless diffuse indoor infrared communication systems have as yet large unrealized bandwidths that are not subject to the same regulatory control as radio frequency systems. Usually, well established RF techniques are used to combat channel imperfections for IR implementations. Here, we introduce a novel receiver system based on the multiresolution time-frequency feature extraction capabilities of wavelet analysis, coupled with the well recognized pattern recognition performance of artificial neural networks for mitigating the effects of bandwidth limiting channel-induced distortion.
20 citations