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We present a new image restoration method based on modelling the coefficients of an overcomplete wavelet response to natural images with a mixture of two Gaussian distributions, having non-zero and zero mean respectively, and reflecting the assumption that this response is close to be sparse. Including the observation model, the resulting procedure iterates between image reconstruction from the hard-thresholding...
This paper presents a practical and effective image compression system based on wavelet decomposition and contrast sensitive-SVR (support vector regression) for compressing still images. The kernel function in an SVR plays the central role of implicitly mapping the input vector (through an inner product) into a high-dimensional feature space. We study the different wavelet kernel for image compression...
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