A NOVEL SAR SIDELOBE SUPPRESSION METHOD BASED ON APPROXIMATE GREATEST COMMON DIVISORS

被引：0

作者：

Liu, YanFang ^{[1
]}

Zou, Fei ^{[2
]}

Yang, Wei ^{[1
]}

Zeng, HongCheng ^{[1
]}

Li, ChunSheng ^{[1
]}

机构：

[1] Beihang Univ, Sch Elect & Informat Engn, Beijing, Peoples R China

[2] Beijing Inst Remote Sensing Informat, Beijing, Peoples R China

来源：

2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) | 2022年

基金：

中国国家自然科学基金;

关键词：

Synthetic aperture radar (SAR); sidelobe suppression; point spread function (PSF); image deconvolution; approximate greatest common divisors (AGCD); IMAGE DECONVOLUTION;

D O I：

10.1109/IGARSS46834.2022.9884022

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

Sidelobe suppression is a challenging but crucial issue for SAR image quality enhancement. Inspired by the blind image restoration method based on the approximate greatest common divisor (AGCD) in natural images, a novel SAR sidelobe suppression method is proposed in this paper. Sidelobe suppression is interpreted as image deconvolution with a known PSF. Another SAR image with different PSF is generated by injecting the phase error at first. Then the PSF estimation is introduced into SAR, which is realized by solving the AGCD of two noised polynomials associated with two SAR images. Finally, the sidelobe suppression reduces to the solution of the inverse problem. Experiments on a TerraSAR-X SAR image show that improved results are qualitatively realized in sidelobe suppression and detail preservation in comparison with two existing algorithms.

引用

页码：747 / 750

页数：4

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