A Line Enhancement Algorithm for Infrared Image Based on Ridgelet

Abstract:

In order to well detect target’s line character for infrared image, we propose improving line character in image through using ridgelet transform which is a kind of multiscale geometric analysis tool and it is especially suitable for describing the 2-D signals which have linear or super-plane singularities. This paper briefs the principle of ridgelet transform and explains our enhancement algorithm in some detail. Its core consists of the method of tensile scale of coefficient in Radon transform domain, filtering method in processing of one dimensional wavelet transform and the algorithm steps of improving line character. It reconstructs images and compares with the other traditional method as presented and analyzes scale of coefficient and time complexity. Our enhancement method is proved effective preliminarily by experimental results.

• Periodical: Applied Mechanics and Materials (Volumes 182-183)
• Pages: 1786-1790
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.182-183.1786
• Online since: June 2012
• Authors: Shuang Shi, Shi Ru Qu, Hai Zhao, Fu Long Chen
• Keywords: Radon Transform, Ridgelet, Wavelet Transform (WT)

References

[1] Dale J, Scott D, Dwyer D, et al. Target tracking, movingtarget detection, stabilization and enhancement of airborne video. Proceedings of SPIE, Airborne Intelligence, Surveillance, Reconnaissance(ISR)Systems and Applications II, 2005, 5787: 154-165.

DOI: 10.1117/12.603509

[2] Zhang Rong, Cheng Xingwu, Zhuo Hongyan, et al. Detection algorithm for moving infrared point target in the sky. Infrared and Laser Engineering, 2003, 32(5): 472-475.

[3] Zhou Rong-jun and He Yu-lin. Seismic Safety Appraisal Report of Ya'an-Lugu Freeway for Beijing-Kunming Expressway Project. Chengdu: Sichuan Sast Technology Co. Ltd, (2005).

[4] E. J. Candes. Ridgelet: theory and application. Stanford: Stanford University, (1998).

[5] D. L. Donoho. Orthonormal ridgelet and linear Singularities. SIAM Journal on Mathematical Analysis, 2000, 31(5): 1062-1099.

DOI: 10.1137/s0036141098344403

[6] Donoho D L, Johnstone I M. Ideal spatial adaptation via wavelet shrinkage. Biometrika, 1994, 81: 425-455.

DOI: 10.1093/biomet/81.3.425

[7] Hou Biao, Jiao Li-cheng, and LIU Fang. Image Denoising Based on Ridgelet. Proceedings of the 6th International Conference on Signal Proceeding. Beijing: Posts & Telecommunications Press, 2002: 780-783.

DOI: 10.1109/icosp.2002.1181172

[8] Jia Jian and Jiao Li-cheng. Implementation of Digital Ridgelet Transform and a New Method. Journal of Computer Research and Development, 2006, 43(1): 115-119.

DOI: 10.1360/crad20060118