Application of EM algorithm to image contrast enhancement

The EM (expectation-maximization) algorithm is a broadly applicable method for calculating maximum likelihood estimates given incomplete data. EM algorithms have received considerable attention due to their computation feasibility in tomographic image reconstruction, and parameter estimation. However, it is less recognized that EM algorithms can be equally applicable to image enhancement applications encountered in scanning, reproduction and rendering processes. No past techniques surveyed can incorporate the potentially complex nature of various image formation processes into a simple probability density array as the EM procedure does. In this paper, an image enhancement technique utilizing the EM procedure to model the image formation process is proposed. By dynamically giving a priori probability distribution suited for a specific application environment currently considered, the proposed method provides a general framework for rendering good image quality at the designated resolution for a large class of image formation process