Radiometric Principle-Based Radiometric Normalization Method for SAR Images Mosaic

被引:0
|
作者
Liu, Rui [1 ,2 ,3 ]
Wang, Feng [1 ,2 ,3 ]
Jiao, Niangang [1 ,2 ,3 ]
Yu, Wei [1 ,2 ,3 ]
You, Hongjian [1 ,2 ,3 ]
Liu, Fangjian [1 ,2 ,3 ]
机构
[1] Chinese Acad Sci, Aerosp Informat Res Inst, Beijing 100094, Peoples R China
[2] Chinese Acad Sci, Key Lab Technol Geospatial Informat Proc & Applic, Beijing 100190, Peoples R China
[3] Univ Chinese Acad Sci, Sch Elect Elect & Commun Engn, Beijing 100049, Peoples R China
关键词
Radar polarimetry; Backscatter; Synthetic aperture radar; Microwave radiometry; Surface roughness; Rough surfaces; Radar imaging; Adjustment; Gaofen-3; mosaic; radiometric normalization (RN); synthetic aperture radar (SAR); CALIBRATION; QUALITY; PALSAR;
D O I
10.1109/LGRS.2022.3184746
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
Radiometric normalization (RN) minimizes the radiometric inconsistencies between images in synthetic aperture radar (SAR) mosaic images. However, the radiometric principle of SAR has not been fully considered by the existing methods. To this issue, a radiometric-principle-based RN (RPRN) method is proposed. First, image areas with consistent coverage areas in object space and approximate rough ground surface between images are extracted as adjustment candidates based on the imaging principle. Then, considering the radiometric characteristic of SAR image, all the images are taken as a whole to solve the radiometric adjustment model, which transfers RN into the least-square optimization. Finally, a global quantization strategy is used to ensure radiometric consistency during orthorectification and mosaicking. The experimental results of Gaofen-3 SAR images demonstrate that the proposed method has the best performance and can effectively and stably eliminate the radiometric differences between images.
引用
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页数:5
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