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We developed a method of image preprocessing based on the information entropy, namely, on the information contribution made by each individual pixel to the whole image or to image’s part (i.e., a Point Information Gain; PIG). An idea of the PIG calculation is that an image background remains informatively poor, whereas objects carry relevant information. In one calculation, this method preserves details, highlights edges, and decreases random noise. This paper describes optimization and implementation of the PIG calculation on graphical processing units (GPU) to overcome a high computational burden.