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Night Vision Image Contrast Enhancement Base on Adaptive Dynamic Histogram

Night image enhancement is an active research area nowadays. There have been a lot of techniques proposed in this area. In this paper, we present a contrast enhancement method base on Adaptive Dynamic Histogram Equalization (ADHE) for night vision image. The ADHE firstly decomposed an input image into two subimages based on the energy threshold of the input image. One of the subimage is the set of samples less than or equal the energy threshold T whereas the other one is the set of samples greater than the energy threshold T. Then the ADHE equalizes the subimages independently base on their respective histograms with the constraint that the samples in the formal set are mapped into the range from the minimum gray level to the twice input energy threshold 2T and the samples in the latter set are mapped into the range from 2T to maximum. Thus, the resulting equalized subimages are bounded by each other around the input energy threshold T, which has an effect of preserving brightness. The proposed technique is compared with other present techniques and is better than those due its computational simplicity and fast processing.