  Image enhancement aims at processing an input image so that the visual
content of the output image is more pleasing or more useful for certain
applications. Although histogram equalization is widely used in image
enhancement due to its simplicity and effectiveness, it changes the mean
brightness of the enhanced image and introduces a high level of noise and
distortion. To address these problems, this paper proposes image enhancement
using fuzzy intensity measure and adaptive clipping histogram equalization
(FIMHE). FIMHE uses fuzzy intensity measure to first segment the histogram of
the original image, and then clip the histogram adaptively in order to prevent
excessive image enhancement. Experiments on the Berkeley database and
CVF-UGR-Image database show that FIMHE outperforms state-of-the-art histogram
equalization based methods.
