A fully automatic genetic approach for grayscale image colorization

Abstract EN

Colorization is a computer assisted process of adding color to a monochrome (grayscale) image or movie.

The early published methods to perform the image colorizing rely on heuristic techniques for choosing RGB colors from a global palette and applying them to regions of the target grayscaled image.

The main improvement of the proposed technique is the adoption in a fully automatic way the genetic algorithm as an efficient search method to find best match for each pixel in the target image.

The proposed genetic algorithm evolves a population of randomly selected individuals (that represents a possible color setting for target image using a reference colored source image toward solution that could resemble natural or real colors to the objects of the target scene).

Moreover this study proposes new crossover operator, called Spread out Uniform Crossover (SUX) that turns the recombination scheme of uniform crossover over spreading vital genes at the expense of lethal genes rather than exchanging genes between mating parents to the generated offspring.

The results of the proposed colorization techniques are good and plausible.