Texture Analysis and its Application for Single-Band SAR Thematic Information Extraction

In this paper single-band and single-polarization Radarsat-1 SAR image is used to evaluate image classification with textural analysis. Firstly, the statistic information of sample were analyzed using semivariogram to determine the optimum parameters for textural extraction; Then four textures such as Homogeneity, Mean, Angle Second Moment and Entropy had been calculated based on GLCM, and the image data were processed using Support Vector Machine classification. The results show that the water and settlement areas are extracted accurately with accuracy 99.34% and 82.54%, and the SVM method has better extension ability for SAR image classification; Assisting with textural information, the image classification based on SVM has a obvious enhancement to original SAR, especially for some complex objects such as settlement areas(about increasing accuracy 18%).