Abstract

. Most segmentation algorithms are composed of several procedures: split and merge, small region elimination, boundary smoothing, : : : , each depending on several parameters. The introduction of an energy to minimize leads to a drastic reduction of these parameters. We prove that the most simple segmentation tool, the "region merging" algorithm, made according to the simplest energy, is enough to compute a local energy minimum belonging to a compact class and to achieve the job of most of the tools mentioned above. We explain why "merging" in a variational framework leads to a fast multiscale, multichannel algorithm, with a pyramidal structure. The obtained algorithm is O(n ln n), where n is the number of pixels of the picture. We apply this fast algorithm to make grey level and texture segmentation and we show experimental results. Key words. variational methods, nonnumerical algorithm, image processing, texture discrimination AMS(MOS) subject classifications. 68Q20,68U10, 1. Int...

Citations