A Mathematical Framework for Image Analysis

提出的研究旨在开发和应用图像分析的数学框架。该方法是通过贝叶斯范式。假设正确构思相关场景属性的先验分布可以作为图像处理的有效基础。应用于纹理分割和分类、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.