本文介绍了遥感图像的计算机复合分层分类方法:在用马氏距离判决分类基础上,引入了土壤图、地形图和纹理结构信息以及专家知识,对初始分类结果进行了分层判决。提高了分类精度。

As to visual recognition of an image, the pattern (spatial feature) and hue (spectral feature) of the image are used as well as the relations between spots and other kinds" of informations. So it leads to analyse an image by using knowledges of many subjects and to recognize different spots with different knowledges.The ordinary computer classification in digital image processing has low accuracy because it only depends on the statistical decision. The multi-level classification uses several auxiliary data and expert knowledges to make multi-level decisions on the result of the primary classification which only depends on the statistical decision. The final classification image is a composition of decisions of all the levels.In the land use classification of Nanpi county, Hebei, three kinds of decisions are used: A. Introduing informations of linear objects sush as roads and channels on the topographic map to the classification result; B. According to the difference in information on the image between resident area and cultivated land, using texture energy decision to correct some errors, which result from the overlapping of spectral information of resident area and spring sowing land, in the primary classification; C. Avoiding the mixture parts of artificial grassland and orchard by means of the information of soil types, since the artificial grassland is only planted on the saline-alkali land but orchard can never be there.Composing results of the three level classification mentioned above and the primary classification, we have obtained the final classification image in which the classification accuracy of cultivated land has raised from 73.8% in the primary classification to 96.6% and the orchard from 76.7% to 95%.