Here, the fast image contrast enhancement is achieved based on histogram equalization (HE) both for color images and the gray-level images. A process called Multi-HE is proposed for the gray-level images. In this method, the input image is decomposed into several sub-images and then the classical HE process is applied to each of the sub-images separately. Also two different discrepancy functions are proposed for the purpose of decomposing the input image. Many simulations have been run and they show that both these methods are better in preserving the brightness and producing more natural looking images than other HE methods. Also a generic fast hue-preserving histogram equalization method is proposed in the case of color images. This is based on the RGB color model. It is also based on the proposed generic method us- ing1D and2D histograms. The shift hue-preserving transformations are used to perform the HE and this prevents the appearance of unrealistic colors. Experiments have also been conducted and this method keeps the quality of the output images close to the original but the value of the contrast is 50% greater than the value of the contrast in the original image.
The problem with the HE technique is that it does not preserve the brightness of the input image on the output one. In the application such as that of video surveillance, the generation of non- existing artifacts in the output image is the aim of the application of this method.

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http://scribddoc/17734702/Contrast-Enhancement-in-Digital-Imaging-Using-Histogram-Equalization