EVOLUTIONARY ALGORITHMS FOR TRANSFERRING PROPERTIES BETWEEN IMAGES PART I: GRAYSCALE IMAGE COLORIZATION
Main Article Content
Abstract
In this paper, an evolutionary algorithm (EA) for “colorizing” grayscale images is introduced by
evolving color patch transfer process between a source colored image and a target grayscale image. As
the general problem of inverting a gray palette to a color palette is a severely under-constrained,
ambiguous problem and has no exact, objective solution, human labor and costly semantic knowledge
are required. The presented EA attempts to minimize the amount of human work by automatically
choosing colored patches from the source image and applying their colors to the grayscale patches of
the target image. Furthermore, the best patch matching over all EA parent individuals are recombined
in a single multi-sexual recombination scheme to form a single offspring individual. Mutation, on the
other hand, forms all other EA individuals. The simple technique of the proposed EA can be
successfully and efficiently applied to a variety of images
Article Details
How to Cite
Publication Dates
References
G. Di Blasi, and R. D. Reforgiato, "Fast colorization of gray images", In proceedings of Eurographics Italian Chapte, 2003.
L. F. M. Vieira, R. D. Vilela, and E. R. Nascimento, "Automatically choosing source color images for coloring grayscale images", 16th Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI 2003), Sao Carlos, Brazil. IEEE Computer Society, ISBN 0-7695-2032-4, pp. 151-158, 2003.
E. Reinhard, M. Ashikhmin, B. Gooch, and P. Shirley, "Color transfer between images", IEEE Transactions on Computer Graphics and Applications 21, 5, pp. 34-41, 2001.
A. Hertzmann, C. E. Jacobs, N. Oliver, B. Curless, and D.H. Salesin, "Image analogies", In Proceedings of ACM SIGGRAPH 2002, pp. 341-346.
T. Welsh, M. Ashikhmin, and K. Mueller, "Transferring color to grayscale images", ACM Transactions on Graphics 21, 3 (July) 2002, pp. 277-280.
J.R. Koza, Genetic Programming: on the programming of computers by means of natural selection. Cambridge, MA: MIT Press, 1992.
H.-P. Schwefel, Numerical Optimization of Computer Models. New York: John Wiley & Sons, 1981.
D.E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. New York: Addison Wesley, 1989.