Noise Reduction in SAR Images with Variable Mode CT

Abstract

Multiplicative noise of an image destructs the pixel association and leads to entropy loss. Somehow filters managed to reduce the noise but were not able to reform the image this leads to blurring of the image. To avoid this transform were measured, this results in a satisfactory image reconstruction with less part of information recovery. For this reason, enhancing image was considered, enhancing the image leads to improve entropy value. So, previously redundant and fusing methods were applied to Satellite Aperture Radar (SAR) images. Here we are providing a novel approach of fusing decomposition techniques i.e., Redundant curvelet transform (RFDCT) with variational Mode Decomposition (VMD). This results in the improvement of 11 parametric values and comparing with existing simulations of RFDCT, RFDCT with Empirical Mode Decomposition (EMD).