Adaptive Neighborhood Extended Contrast Enhancement and Its Modifications

Abstract

A new technique for contrast enhancement, namely adaptive neighborhood extended contrast enhancement, and several original modifications on the same are proposed. Developing from the adaptive contrast enhancement algorithm of Beghdadi and Negrate ( Comput. Vision Graphics Image Process. 46, 1989, 162-174), and the adaptive neighborhood histogram equalization algorithm of Paranjape et al. ( CVGIP Graphical Models Image Process. 54(3), 1992, 259-267), the above techniques have been evolved in order to make image enhancement more adaptive and context sensitive. The adaptive neighborhood extended contrast enhancement algorithm, without its other modifications, only combines the features of these two existing algorithms. This algorithm can be used for both image enhancement and de-enhancement and can also be combined with existing procedures such as power variation. To make the algorithm computationally efficient, the computationally efficient adaptive neighborhood extended contrast enhancement procedure is proposed. This modification achieves significant computational speedup without much loss of image quality. The adaptive neighborhood definition extended contrast enhancement procedure is next proposed in order to make the algorithm further adaptive by making its performance independent of its most sensitive parameter. This procedure achieves better identification of different gray level regions by an analysis of the histogram in the locality of every pixel in the image. The experimental results aptly demonstrate the efficacy of the procedure. This technique can be well applied to other contrast enhancement algorithms for improvement of the quality of the enhanced image. Finally, a correction mechanism called repulsion correction is evolved to correct for a specific inability of contrast enhancement algorithms in separating adjacent regions of nearly equal brightness from each other when surrounded by a very large, brighter or darker region.