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	Image matching using a bat algorithm with mutation (EI CONFERENCE) 会议论文 OAI收割 2012 International Conference on Mechatronic Systems and Automation Systems, MSAS 2012, July 21, 2012 - July 21, 2012, Wuhan, China 作者: Zhang J.; Wang G.; Zhang J.; Zhang J. 收藏 \| 浏览/下载：40/0 \| 提交时间：2013/03/25 Due to shortcoming of traditional image matching for computing the fitness for every pixel in the searching space a new bat algorithm with mutation (BAM) is proposed to solve image matching problem and a modification is applied to mutate between bats during the process of the new solutions updating. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for this improved meta-heuristic approach BAM is also presented. To prove the performance of this proposed meta-heuristic method BAM is compared with BA and other population-based optimization methods DE and SGA. The experiment shows that the proposed approach is more effective and feasible in image matching than the other model. (2012) Trans Tech Publications Switzerland.
	The new approach for infrared target tracking based on the particle filter algorithm (EI CONFERENCE) 会议论文 OAI收割 International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China 作者: Sun H.; Han H.-X.; Sun H. 收藏 \| 浏览/下载：60/0 \| 提交时间：2013/03/25 Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring precision and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure but in order to capture the change of the state space it need a certain amount of particles to ensure samples is enough and this number will increase in accompany with dimension and increase exponentially this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining" we expand the classic Mean Shift tracking framework.Based on the previous perspective we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value.Last because of the gray and fusion target motion information this approach also inhibit interference from the background ultimately improve the stability and the real-time of the target track. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
	Compression of remote sensing image based on Listless Zerotree Coding and DPCM (EI CONFERENCE) 会议论文 OAI收割 ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China Chen S.-L.; Huang L.-Q. 收藏 \| 浏览/下载：32/0 \| 提交时间：2013/03/25 The data quantity of remote sensing image is very large. Furthermore the lowest frequency subband contains the main energy of original image and reflects the coarse of original image after remote sensing image is transformed by wavelet so it is very important to the reconstructed image. Therefore a hybrid image compression method based on Listless Zerotree Coding (LZC) and DPCM is presented namely the lowest frequency subband is compressed by DPCM and others are compressed by LZC. LZC is a kind of zerotree coding algorithm for hardware implementation which is based on SPIHT and substitutes two significant bit maps for three lists in SPIHT algorithm. Thereby LZC significantly reduces the memory requirement and complexity during encoding and decoding procedure. But LZC doesn't recognize the significance of grandchild sets so the PSNR values of LZC are lower than SPIHT's and the compression speed drops. It is improved by adding a significant bit map that recognizes the significance of grandchild sets. A comparison reveals that the PSNR results of the hybrid compression method are 2 dB higher than those of LZC and the compression speed is also improved.
	Improved procedure for preparation of covalently bonded cellulose tris-phenylcarbamate chiral stationary phases 期刊论文 OAI收割 chinese journal of chemistry, 2005, 卷号: 23, 期号: 7, 页码: 885-890 作者: Qin, F; Chen, XM; Liu, YQ; Zou, HF; Wang, JD 收藏 \| 浏览/下载：31/0 \| 提交时间：2010/11/30 chiral stationary phase covalently bonding cellulose derivative improved procedure