中间变量松弛技术及其应用

本文介绍了中间变量松弛技术.对于由中间变量不同状态逻辑组合构成的图象分类来 说,这种方法使松弛技术中的相容系数和条件概率估计的复杂性得到简化,并大大减少松弛迭 代的计算量.此方法应用在地形标记分类处理,得到满意的结果.本文还介绍了用图象子块 直方图对初始概率的估计,有助于加速松弛迭代的收敛.

Intermediate-Parameter Relaxation and its Application

An intermediate-parameter relaxation scheme is described in this paper. For classification problems whose labels are based on the combination of intermediate parameters, this scheme has the advantages that the setting of compatibilities and conditional probabilities can be simplified- and the computational complexity be reduced greatly. With this scheme, satisfactory results have been obtained in improving the topographic primal sketch. The estimation of initial probabilities with histograms of subimages is also described. It is proved that this kind of estimation can speed up the convergence of iteration.