An algorithm of extended terrain classification in high resolution SAR images

A target classification algorithm in high resolution and single polarimetric SAR image is presented in this paper. Firstly, a new RCS reconstruction filter based on the modified correlated neighborhood model is used for target and shadow detection. By nonlinear iterated process, the whole image can be classified to "background", "shadow" and "targets". Secondly, a series of morphological operators are used to terrain filtering and edge extraction, and then through modified Hough Transform technology and the measure of slimming lines, line structures of man-made clutters in "target" class are linked and grouped. Finally, with spatial association model, the targets we are interested in are classified.