Speckle Noise Removal of SAR Images Based on 2-Dimensional S-Transform

With its ability to image the earth's surface in nearly all weather conditions, together with its high spatial resolution, Synthetic Aperture Radar (SAR) has shown its potential for classifying and monitoring geographysical parameters both locally and globally. However, SAR images are usually corrupted by the speckle noise. It badly disturbs the extraction and interpretation of the information of the objects, influences the application of the SAR images. So it has important meaning to reduce the speckle noise in the SAR images. In this paper, 2-dimensional S-transform is proposed to remove the speckle noise of SAR images. Firstly, the 2-dimensional S transform algorithm is analyzed and applied to removal speckle noise of RADARSAT images. Then, the flatness index (FI), the edge remaining index (ERI) and primary statistical parameters are used to compare the results among median filtering, average filtering, LEE filtering, FROST filtering, KUAN filtering, GAMMA filtering and 2-dimensional S-transform. The experiment results show that the speckle noise is most effectively restrained using the two dimensional S-transform.