Speckle Reduction in SAR Images using CNN
V. Santhi, Dheshan Mohandass, J. Gnana Jayanthi, Pachiyappan Arulmozhivarman, Raghav Mehra · 2021
The importance of remote sensing has ballooned in the recent decade, due to the increased need for its applications, from commercial and economic, to intelligence and military applications. Synthetic Aperture Radar (SAR), an important remote sensing instrument captures data that are inherently affected with speckle noise due to its coherent imaging, which makes working with SAR data complicated. Therefore, Synthetic Aperture Radar (SAR) images can benefit greatly from good speckle reduction or suppression techniques, making them easier to analyze and utilize their maximum potential. This paper gives a technical review of various speckle filtering approaches for Synthetic Aperture Radar Images (SAR), discussing the drawbacks of the older conventional methods, and the improvements the newer convolutional Neural Networks (CNN) based solutions bring to the table.