中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
国家空间科学中心 [1]
沈阳自动化研究所 [1]
采集方式
OAI收割 [2]
内容类型
会议论文 [1]
期刊论文 [1]
发表日期
2019 [1]
2013 [1]
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Characteristics of High-Energy Proton Responses to Geomagnetic Activities in the Inner Radiation Belt Observed by the RBSP Satellite
期刊论文
OAI收割
JOURNAL OF GEOPHYSICAL RESEARCH-SPACE PHYSICS, 2019, 卷号: 124, 期号: 9, 页码: 7581-7591
作者:
Xu, Jiyao
;
He, Zhaohai
;
Baker, D. N.
;
Roth, Ilan
;
Wang, Chi
  |  
收藏
  |  
浏览/下载:46/0
  |  
提交时间:2019/12/17
inner radiation belt
geomagnetic activities
high-energy proton
prompt responses
one-to-one correspondence
RBSP satellite
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.