One of the most important problems in discrete tomography is to reconstruct function f:a→{0,1}, where a is a finite subset of Z˄n (n ≥2), from the finite set of projections. There are a lot of methods dedicated for this problem, which employ basic methods of discrete mathematic, distribution theory, and even evolutionary algorithms. In this paper, new approach to this problem, based on global extremes analysis, is presented. It is competitive with the other algorithms, due to the fact that, it returns projections identical with the original ones and is most effective in case of images with consistent objects.
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