Medical image enhancement based on nonlinear technique and logarithmic transform coefficient histogram matching

This paper presents a new method of medical image enhancement that improves the visual quality of digital images as well as images that exhibits dark shadows due to limited dynamic range of imaging. In this paper, non linear image enhancement technique is used in transform domain by the way of transform coefficient histogram matching to enhance image. Processing includes global dynamic range correction and local contrast enhancement which is able to enhance the luminance in the dark shadows keeping the overall tonality consistent with that of the input image. Logarithmic transform histogram matching is used which uses the fact that the relation between stimulus and perception is logarithmic. A measure of enhancement based on the transform is used as a tool for evaluating the performance contrast measure with respect of the proposed enhancement technique. The performance of the algorithm is compared quantitatively to classical histogram equalization using the aforementioned measure of enhancement. A number of experimental results over some x-ray and facial images are presented to show the performance of the proposed algorithm alongside classical histogram equalization.