Comparative analysis of VISU shrink and PMD model on SAR images for speckle noise reduction

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Publicado en 3C Tecnología. Edición Especial/Special Issue – Noviembre/November 2021



Removing noise from original image is often the initial step in image analysis. The best de-noising technique should not be only reducing the noise, but do so without blurring or changing the location of the edges. Many approaches have been proposed for noise reduction. Speckle noise can be easily removed by simple method such as partial Differential Equations method (PDEs). In this paper, Perona-Malik Diffusion (PMD) models have been proposed and compared with VISU Shrinkage (VS) method. Although both the methods are seemed to be comparable with removing speckle noise, speckles are more visible to mages processed by VS method. The experimental results show that the PMD model obtains superior performance with the PSNR value of 61.90%, SSI of 0.40, EPI of 0.51 and SSIM of 69.05%. The PSNR value has been increased by 20.2% when compared with VS de-speckling method.


Palabras clave

De-speckling, PDE, Synthetic Aperture Radar, VISU shrink, DWT.

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