Title: Speckle noise reduction in SAR images using type-II neuro-fuzzy approach

Authors: S. Vijayakumar; V. Santhi

Addresses: School of Computer Science and Engineering, VIT University, Vellore, India ' School of Computer Science and Engineering, VIT University, Vellore, India

Abstract: 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.

Keywords: SAR image; speckle noise; fuzzy logic system; artificial neural network; noise reduction; Gaussian model.

DOI: 10.1504/IJAIP.2022.126691

International Journal of Advanced Intelligence Paradigms, 2022 Vol.23 No.3/4, pp.276 - 293

Received: 14 Feb 2017
Accepted: 03 Nov 2017
Published online: 03 Nov 2022 *

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