标题：An efficient multi-resolution variational Retinex scheme for the radiometric correction of airborne remote sensing images作者：Li, Huifang; Wang, Xiaojing; Shen, Huanfeng; Yuan, Qiangqiang; Zhang,Liangpei

来源出版物：INTERNATIONAL JOURNAL OF REMOTE SENSING 卷：37 期：5 页码：1154-1172 DOI: 10.1080/01431161.2016.1145364 出版年：MAR 2016

摘要：The brightness non-uniformity caused by vignetting effects, viewing, and illumination angels in remote sensing images reduces the interpretation precision. A multi-resolution variational Retinex scheme is proposed in this paper to efficiently correct the non-uniform brightness in airborne remote sensing images. This variational Retinex model is non-linear, constrained by the grey-world assumption and the total variation regularization. A Gaussian image pyramid is used to construct the multi-resolution scheme. The multi-resolution scheme reduces the calculation burden and raises the calculation efficiency. The fast split Bregman (SB) iteration method is employed to optimize the proposed non-linear model in each level of the multi-resolution scheme. This decomposes the complicated model into several simple sub-problems and greatly improves the calculation efficiency. The multi-resolution scheme embedded with the SB iteration method was applied to both synthetic and real remote sensing images. The experimental results show that the brightness non-uniformity can be corrected, and the spectral information can be effectively restored. Moreover, the calculation efficiency is raised by about 60-110 times, compared to the traditional single-resolution solving method.

入藏号：WOS:000372795700009

文献类型：Article

语种：English

扩展关键词：COLOR IMAGES; ENHANCEMENT; NORMALIZATION; DECOMPOSITION; RESTORATION; ALGORITHMS; FRAMEWORK; SYSTEM; MODEL

通讯作者地址：Shen, HF, Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China.

电子邮件地址：shenhf@whu.edu.cn

地址：

[Li, Huifang; Shen, Huanfeng] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China.

[Wang, Xiaojing] Baidu Com Times Technol Co Ltd, Beijing, Peoples R China.

[Shen, Huanfeng; Yuan, Qiangqiang; Zhang, Liangpei] Collaborat Innovat Ctr Geospatial Technol, Wuhan, Peoples R China.

[Yuan, Qiangqiang] Wuhan Univ, Sch Geodesy & Geomat, Wuhan 430072, Peoples R China.

[Zhang, Liangpei] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430072, Peoples R China.

研究方向：Remote Sensing; Imaging Science & Photographic Technology

ISSN：0143-1161

eISSN: 1366-5901

影响因子（2014）：1.652