Actually, pursuit techniques have become very popular ; in consequence, they have been very used in many signal and image processing works. Matching Pursuit and High Resolution Pursuit are the most representative pursuit techniques. In this work we introduce some image coding models based on these techniques. These models employ an overcomplete dictionary, which has been determined according to a previous knowledge and some performed tests. From such dictionary, the elements corresponding to the most important image structures are selected. The pursuit techniques, by a similarity measure, perform such selection. Coefficients of selected elements are quantized just when they are chosen in order to minimize error propagation along the process. The set of selected coefficients corresponds to an optimal image decomposition, or a new representation with a reduced quantity of elements. A simple reconstruction algorithm recovers the original image with a high visual quality.
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