An effective adaptive fuzzy filter for speckle noise reduction

SAR is a self-illuminating imaging method that produces high-resolution images in all weather conditions, day and night. Many application scientists have accepted and used SAR pictures. The SAR images, however, are distorted by speckle noise. Random interference of electromagnetic signals scattered by the object surface within one resolution element causes speckle noise. The amount and distribution of noise that corrupts the image are unpredictably large. Traditional noise filters are quantitative in nature and are not well suited to problems involving uncertainty. Uncertainty can be handled through fuzzy logic. A despeckling approach based on non-subsampled contourlet transform is proposed in this study. Non-subsampled filter banks can influence the directionality, anisotropy, and translation invariance of this transform. The two most desirable qualities of noise filters are noise reduction and image detail preservation. PSNR and MSE are used to assess the suggested fuzzy filter's performance. The performance is measured using SAR images with varied degrees of speckle noise. The effective filter has shown to decrease noise while preserving image edges.