A Sub-pixel based Method to Extract and Interpret Information from Image and its Preliminary Application

摘要

Resolving sub-pixel area information extraction has gained increasing attention in the remote sensing community. Automated morphological endmember extraction (AMEE) which integrates spatial and spectral information to select endmembers, is able to provide a relatively good characterization of general landscape conditions. As tradition support vector machine (SVM) predicts only class label, in order to obtain the abundance fractions of targets of interest, SVM method can be combined with pairwise coupling. This paper describes a model which combines SVM approach and AMEE algorithm. One of the main advantages of using this model is that it performs automatic sub-pixel information detection. At last, simulated and real Landsat TM data are used to demonstrate the potential of this approach.