Abstract

Contrast enhancement and brightness preservation are the crucial steps for image quality control for developing informative and visually pleasing images. Histogram equalization based image enhancement tool does not provide the brightness preservation and better contrast enhancement. This may cause loss in diagnostic information in case of medical images. An attempt has been made to integrate range limited and weighted histogram equalization with adaptive gamma correction followed by homomorphic filtering to study the improvement in contrast as well as to preserve the essential details of the image. An image segmentation based on an efficient Otsu’s method has been implemented. The experimental results obtained are found to be optimal for generating enhanced images according to both quantitative estimation and qualitative human visual inspection. An excellent performance in terms maximum entropy preservation, better contrast enhancement and the best visual appearance of low contrast medical images has been achieved.

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