Speckle noise reduction in SAR images using type-II neuro-fuzzy approach
S. Vijayakumar, V. Santhi · International Journal of Advanced Intelligence Paradigms · 2022
Synthetic aperture RADAR (SAR) images play a vital role in remote sensing applications and thus it insists the requirement of quality enhancement as it gets affected with speckle noise. It is a kind of noise that gets multiplied with pixel intensities due to interference of backscattering signal. In this paper, computational intelligence-based approach is proposed to remove speckle noise by preserving edges and texture information. In particular, the proposed system uses type-II neuro-fuzzy approach using pixel neighbourhood topologies. The performance efficiency of the proposed system is proved by comparing its results with existing methods.