Speckle-noise Reduction in Agricultural SAR Images by using Bayesian Methods
The Synthetic Aperture Radar (SAR) plays a very crucial character in agricultural areas for detection and monitoring of agricultural land. One of the best property of SAR that it function without getting affected in inclement weather and also work in night time. SAR emits the microwave towards the targeted surface and pulses hits the surface and backscattered to respective spacecraft with information of the targeted surface but it get inherited a granular pattern which is known as speckle. The speckle-noise is multiplicative in nature which leads to degrade the quality of captured images. There are various techniques has been developed for removing the speckle-noise in agricultural SAR image but most of them only smoothened the edges not preserving the edges of the images thus it’s a most challenging task. In this paper we have made the study about the one of the very popular despeckling methods known as Bayesian methods for obtaining the aim i.e. to precisely suppress the speckle-noise in agricultural SAR images and preserve the fine details such as edges and texture. For measuring the efficiency of these despeckling techniques we have discussed some of the performance metrics such as SNR, PNSR, UIQI, SSIM, LMSE, SC etc.