A Mathematical Framework for Image Analysis

拟议的研究旨在开发和 图像分析的数学框架的应用。 该方法是通过贝叶斯范式。 推定 在相关场景中适当考虑先验分布 属性可以是图像处理的有效基础。 应用是纹理分割和分类， 边界检测、计算机断层扫描和全局图像 分析.

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.