• IEIE Transactions on Smart Processing and Computing
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• v.4 no.5
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• pp.349-353
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• 2015

The conventional intensity histogram does not indicate edge information, which is important in the perception of image contrast. In this paper, we propose a multi-cue histogram (MCH) to represent a collaborative distribution of both the intensity and the edges of an image. Based on the MCH, if the intensity values have high frequency and a large gradient magnitude, they are spread into a larger dynamic range. Otherwise, the intensity values are not strongly stretched. As a result, image details, such as edges and textures, can be enhanced while artifacts and noise can be prevented, as demonstrated in the experimental results.