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Topology Optimization Design Method for Supporting Structures of Optical Reflective Mirrors Based on Zernike Coefficient Optimization Model 期刊论文
Guangzi Xuebao/Acta Photonica Sinica, 2020, 卷号: 49, 期号: 6
作者:  Y.-C. Shi,H.-D. Yan,P. Gong,T. Liu,Q.-L. Wang,L.-C. Cheng,J. Deng and Z.-Y. Liu
收藏  |  浏览/下载：2/0  |  提交时间：2021/07/06
LSS-target detection in complex sky backgrounds 期刊论文
Chinese Optics, 2019, 卷号: 12, 期号: 4, 页码: 853-865
作者:  Y.-F.Wu;  Y.-J.Wang;  H.-J.Sun;  P.-X.Liu
收藏  |  浏览/下载：1/0  |  提交时间：2020/08/24
Critical power and clamping intensity inside a filament in a flame 期刊论文
Optics Express, 2016, 卷号: 24, 期号: 4
作者:  Li, H.;  W. Chu;  H. Zang;  H. Xu;  Y. Cheng and S. L. Chin
收藏  |  浏览/下载：14/0  |  提交时间：2017/09/11
红外多目标实时跟踪方法的研究 学位论文
博士: 中国科学院大学, 2014
穆治亚
收藏  |  浏览/下载：73/0  |  提交时间：2014/08/21
基于焦面图像信息的波前探测技术研究 学位论文
博士: 中国科学院大学, 2014
马鑫雪
收藏  |  浏览/下载：73/0  |  提交时间：2014/08/21
Dynamic assessment of laser-dazzling effects based on the laser power and spot position of multi-frame images 期刊论文
Zhongguo Jiguang/中文 Journal of Lasers, 2014, 卷号: 41, 期号: 11
Qian F.; Sun T.; Guo J.; Wang T.
收藏  |  浏览/下载：11/0  |  提交时间：2015/04/24
The research of multi-frame target recognition based on laser active imaging 会议论文
5th International Symposium on Photoelectronic Detection and Imaging, ISPDI 2013, June 25, 2013 - June 27, 2013, Beijing, China, June 25, 2013 - June 27, 2013
Wang C.-J.; Sun T.; Wang T.-F.; Chen J.
收藏  |  浏览/下载：9/0  |  提交时间：2014/05/15
Displacement estimation by the phase-shiftings of fourier transform in present white noise (EI CONFERENCE) 会议论文
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
Wu Y.-H.; Yu Q.-Y.
收藏  |  浏览/下载：18/0  |  提交时间：2013/03/25
Displacement estimation is a fundamental problem in Real-time video image processing. It can be typically approached by theories based on features in spatial domain. This paper presents an algorithm which improves the theory for estimating the moving object's displacement in spatial domain by its Fourier transform frequency spectrum. Because of the characters of Fourier transform  the result is based on all the features in the image. Utilizing shift theorem of Fourier transform and auto-registration  the algorithm employs the phase spectrum difference in polar coordinate of two frame images sequence with the moving target1  2. The method needn't transform frequency spectrum to spatial domain after calculation comparing with the traditional algorithm which has to search Direc peak  and it reduces processing time. Since the technique proposed uses all the image information  including all the white noise in the image especially  and it's hard to overcome the aliasing from noises  but the technique can be an effective way to analyze the result in little white noise by the different characters between high and low frequency bands. It can give the displacement of moving target within 1 pixel of accuracy. Experimental evidence of this performance is presented  and the mathematical reasons behind these characteristics are explained in depth. It is proved that the algorithm is fast and simple and can be used in image tracking and video image processing.  
Intelligent MRTD testing for thermal imaging system using ANN (EI CONFERENCE) 会议论文
ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China
Sun J.; Ma D.
收藏  |  浏览/下载：17/0  |  提交时间：2013/03/25
The Minimum Resolvable Temperature Difference (MRTD) is the most widely accepted figure for describing the performance of a thermal imaging system. Many models have been proposed to predict it. The MRTD testing is a psychophysical task  for which biases are unavoidable. It requires laboratory conditions such as normal air condition and a constant temperature. It also needs expensive measuring equipments and takes a considerable period of time. Especially when measuring imagers of the same type  the test is time consuming. So an automated and intelligent measurement method should be discussed. This paper adopts the concept of automated MRTD testing using boundary contour system and fuzzy ARTMAP  but uses different methods. It describes an Automated MRTD Testing procedure basing on Back-Propagation Network. Firstly  we use frame grabber to capture the 4-bar target image data. Then according to image gray scale  we segment the image to get 4-bar place and extract feature vector representing the image characteristic and human detection ability. These feature sets  along with known target visibility  are used to train the ANN (Artificial Neural Networks). Actually it is a nonlinear classification (of input dimensions) of the image series using ANN. Our task is to justify if image is resolvable or uncertainty. Then the trained ANN will emulate observer performance in determining MRTD. This method can reduce the uncertainties between observers and long time dependent factors by standardization. This paper will introduce the feature extraction algorithm  demonstrate the feasibility of the whole process and give the accuracy of MRTD measurement.  

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