IMPROVED MAN-COMPUTER INTERACTIVE CLASSIFICATION OF CLOUDS BASED ON BISPECTRAL SATELLITE IMAGERY

In this paper,improvement on man-computer interactive classification of clouds based onhispeetral satellite imagery has been synthesized by using the maximum likelihood automaticclustering(MLAC)and the unit feature space classification(UFSC)approaches.The improvedclassification not only shortens the time of sample-training in UFSC method,but also eliminatesthe inevitable shortcomings of the MLAC method.(e.g.,1.sample selecting and training isconfined only to one cloud image:2.the result of clustering is pretty sensitive to the selection ofinitial cluster center:3.the actual classification basically can not satisfy the supposition of normaldistribution required by MLAC method;4.errors in classification are difficult to be modified.)Moreover,it makes full use of the professionals’accumulated knowledge and experience of visualcloud classifications and the cloud report of ground observation,having ensured both the higheraccuracy of classification and its wide application as well.