An Effective Adaptive Fuzzy Filter for SAR Image Noise Reduction

In this paper, I propose a fuzzy logic methodology for the problem of uncertainty in an innovative manner. The foundation of this strategy is synthetic aperture radar, which can provide high-resolution images in any conditions, day or night. Speckle noise, which is produced by the random interference of EM signals disseminated by the object's plane within one resolution group, distorts the SAR images, but application scientists have widely accepted and utilized them. It is impossible to predict how much visual cacophony will appear or where its concentration will be. The quantitative nature of the majority of extant noise filters disqualifies them for use with uncertain data. According to this study, non-sub sampling filter banks may effect the transform's directionality, anisotropy, and translation invariance. This filter has been demonstrated to effectively reduce noise while preserving image edge quality.