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科研机构
沈阳自动化研究所 [5]
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会议论文 [5]
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2016 [1]
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内容类型:会议论文
专题:沈阳自动化研究所
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No-Reference Image Quality Assessment for Defocus Restoration
会议论文
1st International Conference on Multimedia and Image Processing, ICMIP 2016, Bandar Seri Begawan, Brunei, June 1-3, 2016
作者:
Zhang CS(张程硕)
;
Shi ZL(史泽林)
;
Xu BS(徐保树)
;
Feng B(冯斌)
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浏览/下载:28/0
  |  
提交时间:2016/11/06
No-reference image quality assessment
defocus
image restoration
Can wavefront coding infrared imaging system achieve decoded images approximating to in-focus infrared images?
会议论文
Photoelectronic Technology Committee Conferences, Hefei, China, June 14, 2015
作者:
Feng B(冯斌)
;
Zhang CS(张程硕)
;
Xu BS(徐保树)
;
Shi ZL(史泽林)
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  |  
浏览/下载:32/0
  |  
提交时间:2015/12/16
Wavefront coding
optical coding
digital decoding
infrared imaging
athermalization
Infrared lens thermal effect: equivalent focal shift and calculating model
会议论文
International Symposium on Optoelectronic Technology and Application 2014, Beijing, China, May 13-15, 2014
作者:
Zhang CS(张程硕)
;
Shi ZL(史泽林)
;
Feng B(冯斌)
;
Xu BS(徐保树)
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  |  
浏览/下载:33/0
  |  
提交时间:2014/12/29
Infrared systems
Thermal effect
Defocus
Aberrations
Wave aberration
A line mapping based automatic registration algorithm of infrared and visible images
会议论文
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)
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浏览/下载:24/0
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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.
非各向同性高斯模糊图像不变距离
会议论文
第十届全国光电技术学术交流会, 北京, 2012年6月12日至15日
作者:
张程硕
;
刘云鹏
;
史泽林
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浏览/下载:28/0
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提交时间:2012/12/28
非各向同性高斯滤波
图像商空间
模糊指标
不变距离
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