Edge preserving image enhancement using anisotropic diffusion

Enhancing an image in such a way that maintains image edges is a difficult problem. Many current methods for image enhancement either smooth edges on a small scale while improving contrast on a global scale or enhance edges on a large scale while amplifying noise on a small scale. One method which has been proposed for overcoming this is anisotropic diffusion, which views each image pixel as an energy sync which interacts with the surrounding pixels based upon the differences in pixel intensities and conductance values calculated from local edge estimates. In this paper, we propose a novel image enhancement method which makes use of these smoothed images produced by diffusion methods. The basic steps of this algorithm are: a) decompose an image into a smoothed image and a difference image, for example by using anisotropic diffusion or as in Lee's Algorithm [14]; b) apply two image enhancement algorithms, such as alpha rooting [7] or logarithmic transform shifting [15]; c) fuse these images together, for example by weighting the two enhanced images and summing them for the final image. Computer simulations comparing the results of the proposed method and current state-of-the-art enhancement methods will be presented. These simulations show the higher performance, both on the basis of subjective evaluation and objective measures, of the proposed method over current methods.