Title
An Iterative SAR Image Filtering Method Using Nonlocal Sparse Model
Abstract
In this letter, we propose an iterative synthetic aperture radar (SAR) image filtering method using the nonlocal sparse model. The original SAR image is first transformed to the logarithmic SAR image domain. Then, we use the nonlocal sparse model and the iterative regularization technique to denoise the log-intensity image. In each iteration, we update the noisy image and then estimate the noise variance. For each patch in the noisy image, we find several similar patches and stack them together in a group. This noisy group is filtered by simultaneous sparse coding. Then, all of the filtered groups are aggregated to form the denoised image. Experimental results demonstrate that the proposed method can achieve state-of-the-art SAR image despeckling performance.
Year
DOI
Venue
2015
10.1109/LGRS.2015.2417551
Geoscience and Remote Sensing Letters, IEEE  
Keywords
Field
DocType
despeckling,iterative regularization,nonlocal sparse model,synthetic aperture radar (sar),iterative methods,noise measurement,synthetic aperture radar,noise,speckle,dictionaries,remote sensing
Speckle pattern,Noise measurement,Synthetic aperture radar,Remote sensing,Regularization (mathematics),Artificial intelligence,Logarithm,Computer vision,Pattern recognition,Neural coding,Iterative method,Filter (signal processing),Mathematics
Journal
Volume
Issue
ISSN
PP
99
1545-598X
Citations 
PageRank 
References 
9
0.54
22
Authors
4
Name
Order
Citations
PageRank
Bin Xu113323.23
Yi Cui2482.32
zenghui li3292.35
Jian Yang448364.80