A MAP Approach With Huber-MRF for Synthetic Aperture Interferometric Radiometer

被引：0
|
作者：
Zhu, Ting [1 ]
Yang, Xiaocheng [1 ]
Yan, Jingye [2 ]
Wu, Lin [2 ]
Jiang, Mingfeng [1 ]
Wei, Bo [1 ]
机构：
[1] Zhejiang Sci Tech Univ, Sch Comp Sci & Technol, Hangzhou 310018, Peoples R China
[2] Chinese Acad Sci, Natl Space Sci Ctr, State Key Lab Space Weather, Beijing 100190, Peoples R China
来源：
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2024年 / 21卷
基金：
中国国家自然科学基金;
关键词：
Bayes methods; Inverse problems; Image reconstruction; Brightness temperature; Probability density function; Radiometry; Discrete wavelet transforms; Huber function; interferometric radiometer; inverse problem; maximum a posteriori (MAP); synthetic aperture;
D O I：
10.1109/LGRS.2024.3433029
中图分类号：
P3 [地球物理学]; P59 [地球化学];
学科分类号：
0708 ; 070902 ;
摘要：
Reconstructing the brightness temperature map from the visibilities in synthetic aperture interferometric radiometers (SAIRs) has been proved to be an ill-posed inverse problem. The regularization methods are crucial to effectively overcome the ill-condition of the inverse problem. This letter presents a maximum a posteriori (MAP) approach for retrieving the accurate brightness temperature map in SAIRs. Furthermore, edge-preserving regularization using a Huber-Markov random field (Huber-MRF) model is used to provide a stable solution and eliminate the oscillation artifacts. Numerical experiment results and quantitative analyses verify the effectiveness of the proposed method.
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页数：5
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