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Research on Deep Learning Denoising Method in an Ultra-Fast All-Optical Solid-State Framing Camera 会议论文
Dublin, Ireland, 2021-07-19
作者:  Zhou, Jian;  Wang, Zhuping;  Wang, Tao;  Yang, Qing;  Wen, Keyao
收藏  |  浏览/下载：28/0  |  提交时间：2021/09/03
Strong restrictions on the trait range of co-occurring species in the newly created riparian zone of the Three Gorges Reservoir Area, China 期刊论文
JOURNAL OF PLANT ECOLOGY, 2019, 卷号: 12, 期号: 5, 页码: 825-833
作者:  Zhang, Aiying;  Cornwell, Will;  Li, Zhaojia;  Xiong, Gaoming;  Fan, Dayong
收藏  |  浏览/下载：13/0  |  提交时间：2022/01/06
Image de-noising based on weight improved non-local means filtering algorithm 会议论文
2018 INTERNATIONAL CONFERENCE ON IMAGE AND VIDEO PROCESSING, AND ARTIFICIAL INTELLIGENCE, 2018-01-01
作者:  Guo Chen-long;  Tian Yu;  Wang Wei;  Zheng Haiyan
收藏  |  浏览/下载：11/0  |  提交时间：2019/12/02
Image de-noising based on weight improved non-local means filtering algorithm 会议论文
2018 INTERNATIONAL CONFERENCE ON IMAGE AND VIDEO PROCESSING, AND ARTIFICIAL INTELLIGENCE, 2018-01-01
作者:  Guo Chen-long[1];  Tian Yu[2];  Wang Wei[3];  Zheng Haiyan[4]
收藏  |  浏览/下载：9/0  |  提交时间：2019/04/22
修正巴特沃斯函数快速图像降噪方法 期刊论文
兰州大学学报(自然科学版), 2014, 卷号: 50, 期号: 1, 页码: 122-127
作者:  刘岳巍
收藏  |  浏览/下载：2/0  |  提交时间：2016/07/28
Multiscale non-parametric level set segmentation of ultrasound echocardiography 期刊论文
Hsi-An Chiao Tung Ta Hsueh/Journal of Xi'an Jiaotong University, 2013, 卷号: 47, 期号: [db:dc_citation_issue], 页码: 53-57+96
作者:  Gao, Yanhua;  Liu, Yuhuan;  Yu, Gang
收藏  |  浏览/下载：3/0  |  提交时间：2019/12/03
The new approach for infrared target tracking based on the particle filter algorithm (EI CONFERENCE) 会议论文
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
Sun H.; Han H.-X.
收藏  |  浏览/下载：50/0  |  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).  
基于模板匹配的天体光谱自动处理方法研究 学位论文
工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2006
作者:  段福庆
收藏  |  浏览/下载：81/0  |  提交时间：2015/09/02
Mean shift based auto-extraction of spectral lines for non-emission-line objects 期刊论文
SPECTROSCOPY AND SPECTRAL ANALYSIS, 2005, 卷号: 25, 期号: 11, 页码: 1884-1888
作者:  Duan, FQ;  Wu, FC;  Luo, AL;  Zhao, YH
收藏  |  浏览/下载：11/0  |  提交时间：2015/11/06

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