Using BayesShrink, BiShrink, Weighted BayesShrink, and Weighted BiShrink in NSST and SWT for Despeckling SAR Images
نویسندگان
چکیده
منابع مشابه
Using BayesShrink, BiShrink, Weighted BayesShrink, and Weighted BiShrink in NSST and SWT for Despeckling SAR Images
Synthetic aperture radar (SAR) images are inherently degraded by multiplicative speckle noise where thresholdingbased 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 has been shown that the coefficients of nonsubsampled shearlet transform (NSST) are sparser than those of ...
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15 صفحه اولBayesShrink Ridgelets for Image Denoising
The wavelet transform has been employed as an efficient method in image denoising via wavelet thresholding and shrinkage. The ridgelet transform was recently introduced as an alternative to the wavelet representation of two dimensional signals and image data. In this paper, a BayesShrink ridgelet denoising technique is proposed and its denoising performance is compared with a previous VisuShrin...
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Synthetic Aperture Radar (SAR) is a satellite imaging technology. It produces high resolution images and can be used in varied atmospheric conditions. It can be used under all weather conditions. SAR images are generally affected with granular noise termed as speckle noise. Speckle degrades the spatial resolution, contrast of the image, decreases object detectability and causes inconvenience to...
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ژورنال
عنوان ژورنال: EURASIP Journal on Image and Video Processing
سال: 2018
ISSN: 1687-5281
DOI: 10.1186/s13640-018-0244-3