Titlebook: Wavelets in Signal and Image Analysis; From Theory to Pract Arthur A. Petrosian,Fran?ois G. Meyer Book 2001 Springer Science+Business Media

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Transform Coding of Signals with Bounded Finite Differences: from Fourier to Walsh, to Wavelets 60-s, facilitated the use of transform coding methods for redundancy elimination and efficient data representation. In order to determine the optimal zonal sampling method for a given transform, it is necessary to derive estimates of the transform spectra on a class of input signals. We present a u

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Multi-Layered Image Representationchnique for images. An image is parsed into a superposition of coherent layers: smooth-regions layer, textures layer, etc. The multi-layered decomposition algorithm consists in a cascade of compressions applied successively to the image itself and to the residuals that resulted from the previous com

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Image Compression Through Level Lines and Wavelet Packets .. The sketch contains all the meaningful edge curves, and the geometry of these edges is precisely detected and coded using level lines. The residue . = . - . contains all the microtextures, and it is compressed by means of a wavelet packet representation. By splitting the information contained in

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Image Compression Using Spline Based Wavelet Transforms of discrete interpolatory splines. These filters outperform the traditional biorthogonal 9/7 filters which are frequenty used in wavelet based compression. The new filters and the biorthogonal 9/7 are incorporated into SPIHT in order to measure and compare their performance with one well known code

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