Agricultural SAR Images Despeckling by using non Bayesian Methods

Abstract

In the last few years, the agricultural synthetic aperture radar (SAR) image has become a popular and important application in comparison to optical satellite images such as crop identification, monitoring, and estimation due to its robustness to work in inclement climate conditions. Whenever the SAR captures the images the granular patterns get inherited with the image that’s   known as speckle-noise. The speckle-noise leads to affects the entire characteristics of the captured images, because speckle-noise itself carries the important information, with prejudice and hence obstructs the identification and crucial information present in the agricultural SAR images. Thus, it has become very crucial to remove the speckle-noise in agricultural SAR images by employing suitable techniques that efficiently remove the speckle-noise in agricultural SAR images. The non-Bayesian methods are very efficiently remove the speckle-noise and gives very precise due to their characteristics. The great features of non-Bayesian methods that not only remove the speckle-noise but also preserve the fine details of agricultural SAR images such as edges, texture etc. There are many despeckling techniques present nowadays but most of them only smoothened the edges not enhanced the edges. These all the characteristics of the non-Bayesian methods clearly show that it give very robust system for obtaining the precise results of despeckling.