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Color transfer is a technical means of changing the appearance of an image (source image) such that the image has characteristics similar to those of a specified image (target image). There exist first-order statistics-based and geometry-based color transfer methods. These color transfer methods can be applied in different color spaces via space transformation. In this report, we review the fundamental principles of two color transfer methods in different color spaces and present a comprehensive comparative study on color transfer using statistical and geometrical methods in different color spaces. We assess the quality of color transfer by computing the consistency between the normalized histograms of the source image and target image and discuss the performance of each method for different color spaces. Our experiments show that the best color space is the RLAB color space while the geometrical method is quantitatively better than the statistical method for most of a large number of images.

Statistical and Geometrical Methods: A Comparative Study on Color Transfer to Dark Image