Adaptive Total Variation Regularization Based SAR Image Despeckling and Despeckling Evaluation Index

We introduce a total variation (TV) regularization model for synthetic aperture radar (SAR) image despeckling. A dual-formulation-based adaptive TV (ATV) regularization method is applied to solve the TV regularization. The parameter adaptation of the TV regularization is performed based on the noise...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2015-05, Vol.53 (5), p.2765-2774
Main Authors: Zhao, Yao, Liu, Jian Guo, Zhang, Bingchen, Hong, Wen, Wu, Yi-Rong
Format: Article
Language:English
Subjects:
Adaptive total variation (ATV) regularization
All terrain vehicles
Assessments
despeckling
Estimation
evaluation index
Image edge detection
Image quality
Indexes
Noise
Preserves
Regularization
Regularization methods
Sharpness
Synthetic aperture radar
synthetic aperture radar (SAR)
Television
Transforms
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Summary:We introduce a total variation (TV) regularization model for synthetic aperture radar (SAR) image despeckling. A dual-formulation-based adaptive TV (ATV) regularization method is applied to solve the TV regularization. The parameter adaptation of the TV regularization is performed based on the noise level estimated via wavelets. The TV-regularization-based image restoration model has a good performance in preserving image sharpness and edges while removing noises, and it is therefore effective for edge preserve SAR image despeckling. Experiments have been carried out using optical images contaminated with artificial speckles first and then SAR images. A despeckling evaluation index (DEI) is designed to assess the effectiveness of edge preserve despeckling on SAR images, which is based on the ratio of the standard deviations of two neighborhood areas of different sizes of a pixel. Experimental results show that the proposed ATV method can effectively suppress SAR image speckles without compromising the edge sharpness of image features according to both subjective visual assessment of image quality and objective evaluation using DEI.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2014.2364525