A High-resolution Image Reconstruction Technology Based on G-matrix and Fourier Transform

Siyuan Du, F. Zhao, Jiakai He, Xiong Chen, Lifei Jiang
{"title":"A High-resolution Image Reconstruction Technology Based on G-matrix and Fourier Transform","authors":"Siyuan Du, F. Zhao, Jiakai He, Xiong Chen, Lifei Jiang","doi":"10.1109/CISS57580.2022.9971364","DOIUrl":null,"url":null,"abstract":"Since solving the inversion equation of synthetic aperture image reconstruction is an ill-posed mathematical problem, in order to meet the needs of high-precision reconstruction of scene brightness temperature images during ground detection, the mechanism analysis and algorithm research of high-resolution brightness temperature reconstruction is carried out. In this paper, various resolution-enhanced inversion algorithms such as statistical inversion are analyzed, and the synthetic aperture response is classified. The direct-current (DC) component of the synthetic aperture response is processed by regularized G matrix inversion, and the alternating (AC) component of the synthetic aperture is processed by Fourier inversion, which reduces the bandwidth of the point spread function, solves the problem of sensitivity deterioration when the resolution is increased, and improves the image quality and result correlation, enabling high-resolution image reconstruction. The overall research is verified by numerical calculation of the standard mean error and root mean square error of synthetic aperture inversion brightness temperature image.","PeriodicalId":331510,"journal":{"name":"2022 3rd China International SAR Symposium (CISS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 3rd China International SAR Symposium (CISS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISS57580.2022.9971364","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Since solving the inversion equation of synthetic aperture image reconstruction is an ill-posed mathematical problem, in order to meet the needs of high-precision reconstruction of scene brightness temperature images during ground detection, the mechanism analysis and algorithm research of high-resolution brightness temperature reconstruction is carried out. In this paper, various resolution-enhanced inversion algorithms such as statistical inversion are analyzed, and the synthetic aperture response is classified. The direct-current (DC) component of the synthetic aperture response is processed by regularized G matrix inversion, and the alternating (AC) component of the synthetic aperture is processed by Fourier inversion, which reduces the bandwidth of the point spread function, solves the problem of sensitivity deterioration when the resolution is increased, and improves the image quality and result correlation, enabling high-resolution image reconstruction. The overall research is verified by numerical calculation of the standard mean error and root mean square error of synthetic aperture inversion brightness temperature image.
基于g矩阵和傅里叶变换的高分辨率图像重建技术
由于合成孔径图像重建反演方程的求解是一个病态数学问题,为了满足地面探测过程中场景亮度温度图像高精度重建的需要,开展了高分辨率亮度温度重建的机理分析和算法研究。本文分析了统计反演等各种分辨率增强反演算法,并对合成孔径响应进行了分类。对合成孔径响应的直流(DC)分量进行正则化G矩阵反演处理,对合成孔径的交流(AC)分量进行傅里叶反演处理,减小了点扩散函数的带宽,解决了分辨率增加时灵敏度下降的问题,提高了图像质量和结果相关性,实现了高分辨率图像重建。通过对合成孔径反演亮度温度图像的标准误差和均方根误差的数值计算,验证了整体研究的正确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信