A Study on Speckle Removal Techniques for Sentinel-1A SAR Data Over Sundarbans, Mangrove Forest, India

Abstract

In this study speckle noise is removed from Sentinel-1A synthetic aperture radar (SAR) image of Sundarbans mangrove forest of West Bengal, India. Several adaptive and non-adaptive filters such as Median, Frost, Lee, Gamma maximum a posteriori (MAP) and Boxcar filter are compared for their capability in removing speckle noise. The output obtained from filtering processes are compared using visual interpretation and quantitative measures such as mean squared error, average difference, and peak signal to noise ratio, etc. The results show that boxcar filter performs better than other methods for removal of speckle noise while preserving edges of objects in the image visually.