Results 131 to 140 of about 41,898 (162)
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Color Quantization by Multiresolution Analysis
2009A color quantization method is presented, which is based on the analysis of the histogram at different resolutions computed on a Gaussian pyramid of the input image. Criteria based on persistence and dominance of peaks and pits of the histograms are introduced to detect the modes in the histogram of the input image and to define the reduced colormap ...
Ramella G, Sanniti di Baja G
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Multiresolution Analysis for Image Compression
2006With the advent of the multimedia era and the growth of digital packet networks, the total amount of image data accessed and exchanged by users daily has reached the huge value of several petabytes. Therefore, the compression of continuous-tone still images, either grayscale or color, has grown tremendously in importance.
ALPARONE, LUCIANO +2 more
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Smooth Multiresolution Analysis
2002The axiomatic framework of multiresolution analysis is Fourier analysis in L 2, and the convergence of the wavelet expansion is therefore in the L 2-norm. The smoothness properties of the scaling function and of the mother wavelet are, however, of great interest to obtain fast L 2-convergence of the wavelet expansion, or to obtain pointwise convergence
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About Nonstationary Multiresolution Analysis and Wavelets
Results in Mathematics, 2011Let \(\psi^{(j)} \in L^2(\mathbb R)\) and \(\psi_{j,k} = 2^{j/2}\,\psi^{(j)}(2^j\cdot -k)\) for \(j,k\in \mathbb Z\) be given. In the nonstationary case, \(\psi^{(j)}\) are called mother wavelets, if \(\{\psi_{j,k};\,j,k\in \mathbb Z\}\) is an orthonormal basis of \(L^2(\mathbb R)\).
Bastin, Françoise, Simons, Laurent
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Wavelets and Mallat's Multiresolution Analysis
Fundamenta Informaticae, 1998We present a simple proof of Mallat's theorem about wavelet and multiresolution analysis. We do not use Fourier transform and the proof is accesible even for younger undergraduate students.
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Multiresolution Analysis of Connectivity
2005Multiresolution histograms have been used for indexing and retrieval of images. Multiresolution histograms used traditionally are 2d-histograms which encode pixel intensities. Earlier we proposed a method for decomposing images by connectivity. In this paper, we propose to encode centroidal distances of an image in multiresolution histograms; the image
Atul Sajjanhar +3 more
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Wavelets; Multiresolution Analysis
2016It has been shown in Chap. 12 on time-frequency analysis that how decomposition on a wavelet basis allows highlighting effectively changes with time of the properties of a signal. Wavelet bases with compact support, which could be used by simple filtering operations, have been searched.
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Nonlinear vector multiresolution analysis
Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154), 2002We explore the use of multiresolution analysis for vector signals, such as multispectral images or stock market portfolio time series. These signals often contain local correlations among components that are overlooked in a component-by-component analysis.
M. Gupta, A. Gilbert
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Multiresolution analysis of DEM
SPIE Proceedings, 2004Digital Elevation Models (DEM) have become important tools in many remote sensing applications, such as classification, defense, Geographic Information Systems, etc. But they are complex products to generate and they are still pervaded with errors and artifacts due to the generation techniques themselves or atmospheric problems.
Pauline Audenino, Mihai Datcu
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Frame Multiresolution Analysis
2003The introduction of multiresolution analysis by Mallat and Meyer was the beginning of a new era; the short descriptions in Section 3.9 and Section 4.3 only give a glimpse of the research activity based on this new tool, aiming at construction of orthonormal bases \( \{\psi _{j,k}\}_{j,k\in \mathbb{Z}}. \)
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