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Histogram equalization (HE) is a simple and effective method for contrast enhancement as it can automatically define the gray-level transformation function based on the distribution of gray levels included in an image. HE fails to produce satisfactory results for a broad variety of low-contrast images because HE does not use the spatial features included in the input image. This paper proposes a novel contrast enhancement method using not only the conventional histogram but also the differential gray-level histogram of the input image. The differential gray-level histogram contains edge information from the input image. Edge information is one of the important spatial features of the image. We can extract the regions that are to be emphasized by using both the conventional histogram and the differential gray-level histogram. The input histogram is modified by the histogram of the extracted regions. The gray-level transformation function is derived using the modified histogram. [ABSTRACT FROM AUTHOR]