Research of sub-pixel location algorithm based on image correlation

被引:0
作者
Li Fuwen [1 ]
Xu Chao [1 ]
Jin Weiqi [1 ]
Wang Xia [1 ]
机构
[1] Beijing Inst Technol, Informat Sci & Technol Coll, Dept Opt, Beijing 100081, Peoples R China
来源
INFRARED MATERIALS, DEVICES, AND APPLICATIONS | 2007年 / 6835卷
关键词
sub-pixel; image correlation; image location; displacement;
D O I
10.1117/12.756513
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Digital image con-elation as a tool for surface deformation measurement has been widely used in the field of experimental mechanics. The method is known to resolve deformation gradient fields with sub-pixel accuracy. In this paper, we address the application of digital image correlation to the image location with sub-pixel accuracy to estimate displacement of multiple frames of video sequences. The estimation effect depends on various factors such as image noise and the correlation algorithm chosen. Algorithms of the sub-pixel location on image are analyzed: Gray-value Interpolation based. Image Correlation and Correlation Coefficient Distribution based Fitting. However, Gray-value Interpolation needs a large amount of computational consumption although has high accuracy and it is apt to be influenced by noisy. Correlation Coefficient Distribution has low accuracy but high effective performance. According to the characteristics of these algorithms, a mix algorithm is introduced to improve both accuracy and computational consumption. The imaging process and algorithm execution are simulated using MATLAB. Further more, we could evaluate the displacements of moving objects between two frames of real video sequences and obtain the reconstructed images through displacement data. The validity of the mixed image location algorithm is obviously verified by comparison between original frames and reconstructed image.
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页数:7
相关论文
共 9 条
[1]  
GLEASON SS, 1990, SPIE, P1386
[2]  
[马少鹏 MA Shaopeng], 2005, [光学技术, Optical Technology], V31, P871
[3]  
Meng L B, 2003, J EXPT MECH, V18, P343
[4]  
PANG B, 1999, ADV MECH, V28, P638
[5]  
PANG B, 2005, ACTA METEOROL SIN, V26, P128
[6]  
SHEN Q, 1991, PATTERN RECOGNITION
[7]   ALGORITHMS FOR SUBPIXEL REGISTRATION [J].
TIAN, Q ;
HUHNS, MN .
COMPUTER VISION GRAPHICS AND IMAGE PROCESSING, 1986, 35 (02) :220-233
[8]  
Yu Q F, 2002, PRECISION MEASUREMEN
[9]  
Zhao LC, 1999, J INFRARED MILLIM W, V18, P407