Contrast enhancement in digital imaging using histogram equalization. (Amélioration du contraste des images numériques par égalisation d'histogrammes)

This work proposes two methodologies for fast image contrast enhancement based on histogram equalization (HE), one for gray-level images, and other for color images. For gray-level images, we propose a technique called Multi-HE, which decomposes the input image into several sub-images, and then applies the classical HE process to each one of them. In order to decompose the input image, we propose two different discrepancy functions, conceiving two new methods. Experimental results show that both methods are better in preserving the brightness and producing more natural looking images than other HE methods. For color images, we introduce a generic fast hue-preserving histogram equalization method based on the RGB color space, and two instantiations of the proposed generic method, using 1D and 2D histograms. HE is performed using shift hue-preserving transformations, avoiding the appearance of unrealistic colors. Experimental results show that the value of the image contrast produced by our methods is in average 50% greater than the value of contrast in the original image, still keeping the quality of the output images close to the original.