Monochrome multitone image approximation with low-dimensional palette

Abstract

The report is devoted to the problem of suboptimal approximation of monochrome multitone image. The proposed approximation consists in replacing the original image tone palette with a reduced size tone palette. The suboptimum approximation is based on the evolutionarily genetic algorithm. The algorithm provides the suboptimal selection of tones for the new palette and its covering range. The weight-dividing strategy of the original monochrome multitone image's frequency diagram of brightness is used to define the initial tones of the new palette and its covering range. These numerical vectors, considered as chromosomes, define the approximated image created by 2 respective chromosomes. The standard genetic operators of mutation is crossed over with the selection strategy, which provides an effective approximation optimization according to the criteria of the least square deviation between pixels of their original tones, when related to the new palette tones. The developed algorithm can be applied to the wide class of problems. Examples are the pattern recognition tasks, image defects detection, and image transformation, for printing equipment. The report illustrates the image approximation of the “on board electronic circuit” with the sub-optimization of the specific algorithm probabilistic parameters.