Abstract
Comparative analysis of VISU shrink and PMD model on SAR images for speckle noise reduction
Highlights
Remote sensing images are captured by various sensors
partial Differential Equations method (PDEs) method has been most broadly used in Synthetic Aperture Radar (SAR) image processing in suppressing speckle noise
The Perona-Malik Diffusion (PMD) model has been proposed for speckle noise reduction
Summary
Remote sensing images are captured by various sensors. The captured images are often degraded by speckle noise called multiplicative noise. Speckle is predominantly due to the meddling of the requiting wave of the transducer aperture. It is one of the most perilous commotions that amend the quality of Synthetic Aperture Radar (SAR) coherent images (Choi & Jeong, 2019) and decreases the potentiality of the images. Speckle noise in SAR image is broadly severe, precipitating difficulties for image interpretation. It is generated because of the coherent processing of backscattered signals from multiple distributed targets of the earth surface
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