Infrared and Visible Image Registration Base on SIFT Features

Abstract:

In the System of Target Tracking Recognition, infrared sensors and visible light sensors are two kinds of the most commonly used sensors; fusion effectively for these two images can greatly enhance the accuracy and reliability of identification. Improving the accuracy of registration in infrared light and visible light images by modifying the SIFT algorithm, allowing infrared images and visible images more quickly and accurately register. The method can produce good results for registration by infrared image histogram equa-lization, reasonable to reduce the level of Gaussian blur in the pyramid establishment process of sift algorithm, appropriate adjustments to thresholds and limits the scope of direction of sub-gradient descriptor. The features are invariant to rotation, image scale and change in illumination.

• Periodical: Key Engineering Materials (Volume 500)
• Pages: 383-389
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.500.383
• Online since: January 2012
• Authors: Kai Wei Yang, Tian Hua Chen, Su Xia Xing, Jing Xian Li
• Keywords: Image Registration, Infrared Image, SIFT Algorithm

References

[1] Yuan Jinsha, Zhao Zhenbing, Gao Qiang, Kong Yinghui, Infrared and visible image registration status and prospects, [J], LASER　&　INFRARED, North China Electric Power University, Baoding, Hebei 2009, 7: 630-670.

[2] Rafael C. Gonzalez, Richard E. Woods, translated by Ruan qiuqi, Ru-an yuzhi etc, Digital image processing(U.S. )[M], Beijing, Electronic Industry Press, (2007).

[3] David G. Lowe, Distinctive Image Features from Scale-Invariant Keypoints, [J], Computer Science Department University of British Columbia Vancouver B. C January 5, 2004: 91-110.

DOI: 10.1023/b:visi.0000029664.99615.94

[4] David G. Lowe, Object Recognition from Local Scale- Invariant Features, [J], Computer Science Department University of British Columbia Vancouver, B.C., V6T 1Z4, Canada, 1999: 1150-1157.

DOI: 10.47886/9781888569445.ch13

[5] M ikolajczyk K, Schmid C, A performance evaluation of local descriptors, [J], IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(10): 1615-1630.

DOI: 10.1109/tpami.2005.188

[6] Tian A-Ling, Zhao Zhenbing, Gao Qiang, Based on SIFT of power equipment infrared and visible image registration method, [J] , Electric Power Science and Engineering , North China Electric Power University Institute of Electrical and Electronic Engineering, Hebei baoding, 2008, 5: 13-15.

DOI: 10.29252/jafm.13.01.30063

[7] Liu Ruizhen, Yu Shiqi. beijing, OpenCV tutorial basics [M], Beijing University of Aeronautics and Astronautics Press, (2007).