Using BayesShrink, BiShrink, Weighted BayesShrink, and Weighted BiShrink in NSST and SWT for Despeckling SAR Images

Using BayesShrink, BiShrink, Weighted BayesShrink, and Weighted BiShrink in NSST and SWT for Despeckling SAR Images

Abstract Synthetic aperture radar (SAR) images are inherently degraded by multiplicative speckle noise where thresholding-based methods in the transform domain are appropriate. Being sparse, the coefficients in the transformed domain play a key role in the performance of any thresholding methods. It...

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Bibliographic Details
Main Authors: Nikou Farhangi, Sedigheh Ghofrani
Format: Article
Language:English
Published: SpringerOpen 2018-01-01
Series:EURASIP Journal on Image and Video Processing
Subjects:
BayesShrink
BiShrink
Weighted BayesShrink
Weighted BiShrink
Nonsubsampled shearlet transform
Stationary wavelet transform
Online Access:http://link.springer.com/article/10.1186/s13640-018-0244-3

Internet

http://link.springer.com/article/10.1186/s13640-018-0244-3

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