本文介绍的SVD分类方法,模拟人眼分辨图像上图斑的机理,对遥感图像进行分类。意在克服常规计算机分类的一些缺点,改善图斑边缘及交界处的混分现象,同时做到均匀大图斑的平滑及孤立小图斑的保留,使分类图上图斑整齐,界限分明,精度高,视觉效果好。因此有较好的实际应用价值。

The SVD classification algorithm introduced in this paper is designed for remote sensing image processing. It intends to classify an image by simulating the procedure of human visual distinguishing spots. This method could avoid some defeats in normal classifications, decrease the mixture appeared at the edge or the juncture of classes, smooth the homogeneous spots and conserve the small isolate spots. The result of this new method presents advantages of regular spots, clear boundaries and high accuracy. It is obviously better than the results obtained by normal classifications and it is of great value in practical application.