中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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浏览/检索结果: 共23条,第1-10条 帮助

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Infrared and visible image fusion based on QNSCT and Guided Filter 期刊论文  OAI收割
Optik, 2022, 卷号: 253
作者:  
Yang, Chenxuan
  |  收藏  |  浏览/下载:68/0  |  提交时间:2022/02/08
Angular Calibration of Visible and Infrared Binocular All-Sky-View Cameras Using Sun Positions 期刊论文  OAI收割
REMOTE SENSING, 2021, 卷号: 13
作者:  
Xie, Wanyi;  Wang, Yiren;  Xia, Yingwei;  Gao, Zhenyu;  Liu, Dong
  |  收藏  |  浏览/下载:58/0  |  提交时间:2021/08/31
Mapping lead concentrations in urban topsoil using proximal and remote sensing data and hybrid statistical approaches 期刊论文  OAI收割
ENVIRONMENTAL POLLUTION, 2021, 卷号: 272, 页码: 10
作者:  
Shi, Tiezhu;  Yang, Chao;  Liu, Huizeng;  Wu, Chao;  Wang, Zhihua
  |  收藏  |  浏览/下载:31/0  |  提交时间:2021/04/25
An improved fusion method of infrared and visible images based on fusionGAN 会议论文  OAI收割
Singapore, Singapore, 2021-05-20
作者:  
Yao, Zhiqiang;  Guo, Huinan;  Ren, Long
  |  收藏  |  浏览/下载:32/0  |  提交时间:2021/07/26
Partial NIR-VIS Heterogeneous Face Recognition With Automatic Saliency Search 期刊论文  OAI收割
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2021, 2021, 卷号: 16, 16, 页码: 5003-5017, 5003-5017
作者:  
Luo, Mandi;  Ma, Xin;  Li, Zhihang;  Cao, Jie;  He, Ran
  |  收藏  |  浏览/下载:29/0  |  提交时间:2021/12/28
A color correction method in uniform color space 会议论文  OAI收割
Xiamen, PEOPLES R CHINA, 2020-08-25
作者:  
Chu Nanqing;  Li Xuyang;  Yi Hongwei;  Ren Zhiguang;  Ma Zixuan
  |  收藏  |  浏览/下载:22/0  |  提交时间:2021/06/04
Robust and Fast Registration of Infrared and Visible Images for Electro-Optical Pod 期刊论文  OAI收割
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2019, 卷号: 66, 期号: 2, 页码: 1335-1344
作者:  
Liu, Xiangzeng;  Ai, Yunfeng;  Tian, Bin;  Cao, Dongpu
  |  收藏  |  浏览/下载:58/0  |  提交时间:2019/12/16
General fusion method for infrared and visual images via latent low-rank representation and local non-subsampled shearlet transform 期刊论文  OAI收割
Infrared Physics & Technology, 2018, 卷号: 92, 页码: 68-77
作者:  
Cheng, B. Y.;  Jin, L. X.;  Li, G. N.
  |  收藏  |  浏览/下载:25/0  |  提交时间:2019/09/17
Image enhancement for outdoor long-range surveillance using IQ-learning multiscale Retinex 期刊论文  OAI收割
IET IMAGE PROCESSING, 2017, 卷号: 11, 期号: 9, 页码: 786-795
作者:  
Liu, Haoting;  Lu, Hanqing;  Zhang, Yu
  |  收藏  |  浏览/下载:46/0  |  提交时间:2018/03/03
A line mapping based automatic registration algorithm of infrared and visible images 会议论文  OAI收割
5th International Symposium on Photoelectronic Detection and Imaging (ISPDI) - Infrared Imaging and Applications, Beijing, June 25-27, 2013
作者:  
Ai R(艾锐);  Shi ZL(史泽林);  Xu DJ(徐德江);  Zhang CS(张程硕)
收藏  |  浏览/下载:36/0  |  提交时间:2013/12/26
There exist complex gray mapping relationships among infrared and visible images because of the different imaging mechanisms. The difficulty of infrared and visible image registration is to find a reasonable similarity definition. In this paper, we develop a novel image similarity called implicit linesegment similarity(ILS) and a registration algorithm of infrared and visible images based on ILS. Essentially, the algorithm achieves image registration by aligning the corresponding line segment features in two images. First, we extract line segment features and record their coordinate positions in one of the images, and map these line segments into the second image based on the geometric transformation model. Then we iteratively maximize the degree of similarity between the line segment features and correspondence regions in the second image to obtain the model parameters. The advantage of doing this is no need directly measuring the gray similarity between the two images. We adopt a multi-resolution analysis method to calculate the model parameters from coarse to fine on Gaussian scale space. The geometric transformation parameters are finally obtained by the improved Powell algorithm. Comparative experiments demonstrate that the proposed algorithm can effectively achieve the automatic registration for infrared and visible images, and under considerable accuracy it makes a more significant improvement on computational efficiency and anti-noise ability than previously proposed algorithms.