Compact image representation from multiscale edges

The edges of an image can be detected at different scales from the local maxima of its wavelet transform. an algorithm is described that reconstructs images from their edges at dyadic scales. The wavelet maxima representation is a novel reorganization of the image information that makes it possible to develop algorithms uniquely based on edges for solving image processing and computer vision problems. The evolution of the wavelet maxima across scales gives a precise characterization of the edge type which can be used for pattern recognition. A coding algorithm is described that selects the most important image edges in order to obtain a compact representation.<
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