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A new video denoising algorithm based on adaptive polyview fusion 会议论文
2014 2nd International Conference on Mechatronics, Robotics and Automation, ICMRA 2014, Zhuhai, China, March 8, 2014 - March 9, 2014
作者: Geng, Xue Feng; Wan, Yi

收藏 | 浏览/下载：2/0 | 提交时间：2017/01/18

Robotics Algorithms Image fusion Video signal processing Better performance De-noising algorithm Fusion methods Local feature Multiple views Region division Video de-noising Video sequences

Precise motion compensation based on weighted sub-pixel image matching (EI CONFERENCE) 会议论文
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, May 24, 2011 - May 26, 2011, Beijing, China
Liang H. G.

收藏 | 浏览/下载：18/0 | 提交时间：2013/03/25

This paper proposed a sub-pixel image correlation algorithm that can get more Precise result its principle is apply the distribute of relativity peak to get weighted multi-pixel comprehensive of location. Image correlation be as to calculates the greyscale relativity of image template and matching image the relativity of correspond location where match best with template will be most high and in its neighbour range the relativity will be still keep high too. We used these pixel in this local area of calculated match point to get sub-pixel accuracy the relativity of every pixel be used as its weight for participate the sub-pixel calculation. The sub-pixel location is more accuracy than the integer one we applied this method to perform background compensation in processing the target detecting for video image sequence. At the end of this paper some experiment data be proposed it proved this sub-pixel image correlation can obtain better result. 2011 SPIE.

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).

Parallel estimation of translation for video stabilization (EI CONFERENCE) 会议论文
2010 6th International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2010, September 23, 2010 - September 25, 2010, Chengdu, China
Wang H.; Liu G.; Dai M.; Liu X.

收藏 | 浏览/下载：94/0 | 提交时间：2013/03/25

Translation motion estimation is the major aspect of video motion compensation especially in two-dimensional turntable. This paper presents a robust parallel estimation algorithm of translation in video stabilization system. The equivalent model of translation that derived is accorded with small rotation angle comparatively. A parallel algorithm based on grey mapping is used in local motion estimation to shorten the estimation time and improve the computation efficiency. After local motion vectors are calculated a fast filter can detect the spurious vectors avoiding possible jerks. The suggested translation estimation algorithm has been implemented on NVIDIA GTX 260 the experimental results show that the average time of the estimation and compensation finished in 16 ms/frame and stabilize 1k1k pixels sequence gray video up to 60 frames/s. 2010 IEEE.

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