The proposed research is aimed at the development and at the application of a mathematical framework for image analysis. The approach is through a Bayesian paradigm. The presumption is that properly conceived prior distribution on relevant scene attributes can be an effective basis for image processing. Applications are to texture segmentation and classification, boundary detection, computerized tomography, and global image analysis.
