中国光学（中英文）2024，Vol.17Issue(6)：1307-1315,9.DOI:10.37188/CO.2024-0193
基于张量分解与非下采样Contourlet变换遥感图像增强
Remote-sensing image enhancement based on tensor decomposition and nonsubsampled Contourlet transform
摘要
Abstract
In the process of remote sensing image acquisition,low quality and lack of important information of image are common problems as the existence of interference information.Traditional image enhancement methods often cannot highlight useful information with high precision and high efficiency because they can-not integrate global information effectively.In order to solve these problems,a remote-sensing image en-hancement method based on tensor decomposition and nonsubsampled Contourlet transform is proposed.The optimized nonsubsampled Contourlet transform is used to decompose the original image,and the high-order tensor is composed of high-frequency detail images in all directions on all scales.Through Bayesian probab-ility tensor completion,the potential factors recognized from the incomplete tensor are used to predict the missing details of the image.Experimental results indicate that the proposed method can recover the missing information more effectively and highlight the feature information of the image.Compared with different im-age enhancement methods,the maximum improvement of signal-to-noise ratio,structure similarity and root mean square error are 27.9％,37.6％and 45.4％,respectively.The proposed method is superior to the com-mon image enhancement methods in quantitative evaluation and visual comparison.关键词
图像增强/Contourlet变换/张量分解/贝叶斯概率张量补全Key words
image enhancement/Contourlet transform/tensor decomposition/bayesian probability tensor completion分类
信息技术与安全科学引用本文复制引用
吴庆玲,石强,杜永盛,雷赛,卢明明..基于张量分解与非下采样Contourlet变换遥感图像增强[J].中国光学（中英文）,2024,17(6):1307-1315,9.基金项目
吉林省科技厅科技发展计划重点项目(No.202401021107GX)Supported by Key Projects of Science and Technology Development Program of Jilin Provincial Science and Technology Department(No.202401021107GX) （No.202401021107GX）
