A novel contrast enhancement method using differential gray-levels histogram

Histogram equalization (HE) is a simple and effective method for contrast enhancement as it can automatically define the gray-levels transformation function based on the distribution of gray-levels included in the image. HE fails to produce satisfactory results for a broad variety of low-contrast images because the HE does not use a spatial feature included in the input image. This paper proposes a novel contrast enhancement method using not only the conventional histogram but also the differential gray-levels histogram of the input image. The differential gray-levels histogram contains edge information of the input image. Edge information is one of the important spatial features of the image. We can identify the regions where are desired to be emphasized by using both the conventional histogram and the differential gray-levels histogram. Thus, for example, the proposed method can emphasize the objects which are buried in shadow or saturation regions efficiently.