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	Vehicle detection and tracking in airborne videos by multi-motion layer analysis 期刊论文 OAI收割 machine vision and applications, 2012, 卷号: 23, 期号: 5, 页码: 921-935 作者: Cao, Xianbin; Lan, Jinhe; Yan, Pingkun; Li, Xuelong 收藏 \| 浏览/下载：28/0 \| 提交时间：2011/09/30 Vehicle detection Frame registration Feature tracking Partial occlusion Motion layer
	Image mosaic technique based on the information of edge (EI CONFERENCE) 会议论文 OAI收割 2012 3rd International Conference on Digital Manufacturing and Automation, ICDMA 2012, July 31, 2012 - August 2, 2012, Guilin, Guangxi, China 作者: Wang Y.-Q. 收藏 \| 浏览/下载：33/0 \| 提交时间：2013/03/25 Image mosaic is an important branch in the field of image processing. This paper designs and realizes an image mosaic technique based on the information of edge. The technology is suitable for engineering application. First of all two images of the adjoining frames are processed by convolution operation get the edge images. And then we cut edge image into pieces and compute their spatial frequency. According to the value of the spatial frequency select reasonable registration model group. We compute correlation strength and the value of movement offset which are the model group and the current frame edge image. We can complete image mosaic by them. We use video sequence which of the resolution is 1024 * 768 do the experiment. The results show that the method has good effect and strong adaptability. Algorithm is high efficiency which running time is 24 ms. It is suitable for real-time processing requirements of the application. This method is an effective mosaic technique which is suitable for engineering application. 2012 IEEE.
	Astronomical image restoration through atmosphere turbulence by lucky imaging (EI CONFERENCE) 会议论文 OAI收割 3rd International Conference on Digital Image Processing, ICDIP 2011, April 15, 2011 - April 17, 2011, Chengdu, China 作者: Zhao J.; Wang J.; Zhang S. 收藏 \| 浏览/下载：27/0 \| 提交时间：2013/03/25 In this paper we develop a lucky imaging system to restore astronomical images through atmosphere turbulence. Our system takes very short exposures on the order of the atmospheric coherence time. The rapidly changing turbulence leads to a very variable point spread function (PSF) and the variability of the PSF leads to some frames having better quality than the rest. Only the best frames are selected aligned and co-added to give a final image with much improved angular resolution. Our system mainly consists of five parts: preprocessing frame selection image registration image reconstruction and image enhancement. Our lucky imaging system has been successfully applied to restore the astronomical images taken by a 1.23m telescope. We have got clear images of moon surface and Jupiter and our system can be demonstrated to greatly improve the imaging resolution through atmospheric turbulence. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
	KLT feature based vehicle detection and tracking in airborne videos 会议论文 OAI收割 7th international conference on image and graphics, icig 2011, hefei, anhui, china, august 12, 2011 - august 15, 2013 CaoXianbin; LanJinhe; YanPingkun; LiXuelong 收藏 \| 浏览/下载：23/0 \| 提交时间：2012/07/09 vehicle detection frame registration feature tracking motion layer temporal differencing
	Displacement estimation by the phase-shiftings of fourier transform in present white noise (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Wu Y.-H. 收藏 \| 浏览/下载：27/0 \| 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.