An Anisotropic Diffusion Adaptive Filter for Image Denoising and Restoration Applied on Satellite Remote Sensing Images
A Case Study
Received: 10 September 2022 | Revised: 1 October 2022 | Accepted: 2 October 2022 | Online: 15 December 2022
Corresponding author: M. Gatcha
This paper proposes an operating approach based on the anisotropic diffusion method to restore and denoise Satellite Remote Sensing Images (SRSIs). The contents of the approach are the motion by mean curvature to detect the noise direction for each degraded pixel and preserve the original edges of the image, and the gradient in the Gaussian kernel which restores the degraded pixel locally, assuring the estimation of its original value and saving the contrast of the image. The algorithm, concluded by our proposed system, treats noised SRSIs regardless of noise type, so better restoration is achieved. Experiments of the proposed system and of other approaches were conducted in MATLAB in order to demonstrate the efficiency of the proposed approach and its performance was confirmed through evaluation with PSNR and SSIM.
Keywords:Image restoration, anisotropic diffusion, regularization, Satellite Remote Sensing Images
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