Hierarchical method for building extraction in urban area’s images using unsharp masking [USM] and Bayesian classifier

Recently, due to the availability of high resolution IKONOS image, classification of remote sensing images from urban area become one of the most attractive topics for scientific researches and papers. In this paper, we address a method for classification of remote sensing (IKONOS) image and especially for the extraction of buildings. First step is applying the unsharp masking [USM] which intensify high frequency components of the original image. Then imagepsilas Laplacian, Bayesian classifier and size filter is used for building discrimination. The accuracy of small and large building classification using unsharp mask filter and Bayesian discrimination function is increased compared with the original qualitative model for Bayesian classification. Experiments indicate promising results about the efficiency of the proposed approach.