Point target detection in space-based infrared (IR) imaging system is an important task in many applications such as IR searching and tracking and remote sensing. Although it has attracted great interest and tremendous efforts during last decades, it remains a challenging problem due to the uncertain heterogeneous background and the limited processing resources on the onboard platform. Aiming at this problem, a novel background suppression method based on multi-direction filtering fusion is proposed in this paper. The process of background prediction for each pixel by this method can be divided into two steps. Firstly, eight predicted values are obtained by using linear filtering methods along eight different directions respectively. Then, Gaussian weighted sum of the eight predicted values is computed to generate the final result. We conduct several groups of experiments on different categories scenes with simulated targets, and the final experimental results demonstrate that our methods can not only obtain state-of-the-art performance on background suppression (especially for heterogeneous backgrounds), but also detect targets accurately with low false alarm rate and high speed in IR point target detection tasks.
1. Wan, M., G. Gu, E. Cao, X. Hu, W. Qian, and K. Ren, "In-frame and inter-frame information based infrared moving small target detection under complex cloud backgrounds," Infrared Physics & Technology, Vol. 76, 455-467, May 1, 2016. doi:10.1016/j.infrared.2016.04.003
2. Deng, L., H. Zhu, C. Tao, and Y. Wei, "Infrared moving point target detection based on spatial-temporal local contrast filter," Infrared Physics & Technology, Vol. 76, 168-173, May 1, 2016. doi:10.1016/j.infrared.2016.02.010
3. Chen, Z., T. Deng, L. Gao, H. Zhou, and S. Luo, "A novel spatial-temporal detection method of dim infrared moving small target," Infrared Physics & Technology, Vol. 66, 84-96, Sept. 1, 2014. doi:10.1016/j.infrared.2014.05.007
4. Zhao, F., H. Lu, Z. Zhang, and S. Xiao, "Complex background suppression based on fusion of morphological open filter and nucleus similar pixels bilateral filter," Infrared Physics & Technology, Vol. 55, 454-461, Nov. 1, 2012. doi:10.1016/j.infrared.2012.07.010
5. Chen, Z., S. Luo, T. Xie, J. Liu, G. Wang, and G. Lei, "A novel infrared small target detection method based on BEMD and local inverse entropy," Infrared Physics & Technology, Vol. 66, 114-124, Sept. 1, 2014. doi:10.1016/j.infrared.2014.05.013
6. Bouwmans, T., "Traditional and recent approaches in background modeling for foreground detection: An overview," Computer Science Review, Vol. 11-12, 31-66, May 1, 2014. doi:10.1016/j.cosrev.2014.04.001
7. Bai, X., S. Zhang, B. Du, Z. Liu, T. Jin, B. Xue, and F. Zhou, "Survey on dim small target detection in clutter background: Wavelet, inter-frame and filter based algorithms," Procedia Engineering, Vol. 15, 479-483, Jan. 1, 2011. doi:10.1016/j.proeng.2011.08.091
8. Hou, W., Z. Lei, Q. Yu, and X. Liu, "Small target detection using main directional suppression high pass filter," Optik - International Journal for Light and Electron Optics, Vol. 125, 3017-3022, Jul. 1, 2014. doi:10.1016/j.ijleo.2013.12.025
9. Deshpande, S. D., M. H. Er, R. Venkateswarlu, and P. Chan, "Max-mean and max-median filters for detection of small targets," SPIE Signal and Data Processing of Small Targets, 74-83, 1999.
10. Bai, X. and F. Zhou, "Analysis of new top-hat transformation and the application for infrared dim small target detection," Pattern Recognition, Vol. 43, 2145-2156, Jun. 1, 2010. doi:10.1016/j.patcog.2009.12.023
11. Zeng, M., J. Li, and Z. Peng, "The design of Top-Hat morphological filter and application to infrared target detection," Infrared Physics & Technology, Vol. 48, 67-76, Apr. 1, 2006. doi:10.1016/j.infrared.2005.04.006
12. Bai, X. and F. Zhou, "Infrared small target enhancement and detection based on modified top-hat transformations," Computers & Electrical Engineering, Vol. 36, 1193-1201, Nov. 1, 2010. doi:10.1016/j.compeleceng.2010.05.008
13. Bae, T., F. Zhang, and I. Kweon, "Edge directional 2D LMS filter for infrared small target detection," Infrared Physics & Technology, Vol. 55, 137-145, Jan. 1, 2012. doi:10.1016/j.infrared.2011.10.006
14. Cao, Y., R. M. Liu, and J. Yang, "Small target detection using two-dimensional least mean square (TDLMS) filter based on neighborhood analysis," International Journal of Infrared and Millimeter Waves, Vol. 29, 188-200, 2008. doi:10.1007/s10762-007-9313-x
15. Xie, K., K. Fu, T. Zhou, J. Zhang, J. Yang, and Q. Wu, "Small target detection based on accumulated center-surround difference measure," Infrared Physics & Technology, Vol. 67, 229-236, Nov. 1, 2014. doi:10.1016/j.infrared.2014.07.006