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FACET REPRERSENTATION OF AN IMAGE AND SEGMENTATION AS SORTING

A fundamental approach to analysis and representation of an Image on a scale between Whole-Image-scale and Pixel-scale is still not well developed in Computer Science. On the other hand, it is clear, that successful manipulation with local image statistics, such as local histograms, local texture features, etc, may provide a powerful tool for Image Processing, Understanding and Multimedia. This paper describes one of the possible ways to construct such an approach, based on a notion of subimages (facets). It is shown, that this approach may provide a competitive results in such applications, as adaptive segmentation, boarder detection, stereoscopic vision and motion tracking. Paper is concentrated on analysis of such local image statistics, as facets' historgams. This method allows, from one hand, to build a non-uniform multiresolution image subdivision and, on another hand, an approximation to semantical tree of a scene. The connection between them may be very useful for Multimedia applications.