Abstract
A novel and simple method for identification of targets in infrared (IR) images is proposed in this chapter. The input image is divided into blocks of fixed size. The saliency map is extracted block-wise in three different ways. In the first approach, the entropy of each block is compared with the global entropy of the image. In the second approach, the energy of each block is compared with the global energy of the image. In the third approach, combined entropy and energy are used. Experimental results show that the combined approach of entropy and energy detects the targets accurately compared to the other two methods. The subjective results show the efficacy of the proposed approach. The objective evaluation measures show the high detection rate and low false alarm rate.
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Russ, J.C.: The Image Processing Handbook. CRC Press, Boca Raton (2006)
Bai, X., Zhou, F.: Analysis of new top-hat transformation and the application for infrared dim small target detection. Pattern Recognit. 43(6), 2145–2156 (2010)
Bai, X., Zhou, F.: Hit-or-miss transform based infrared dim small target enhancement. Opt. Laser Technol. 43(7), 1084–1090 (2011)
Peregrina-Barreto, H., Herrera-Navarro, A.M., Morales-Hernández, L.A., Terol-Villalobos, I.R.: Morphological rational operator for contrast enhancement. J. Opt. Soc. Am. A 28(3), 455–464 (2011)
Sui, X., Chen, Q., Bai, L.: Detection algorithm of targets for infrared search system based on area infrared focal plane array under complicated background. Optik-Int. J. Light Electron. Opt. 123(3), 235–239 (2012)
Khan, J.F., Alam, M.S., Bhuiyan, S.: Automatic target detection in forward-looking infrared imagery via probabilistic neural networks. Appl. Opt. 48(3), 464–476 (2009)
Shaik, J., Iftekharuddin, K.M.: Detection and tracking of targets in infrared images using Bayesian techniques. Opt. Laser Technol. 41(6), 832–842 (2009)
Cao Yuan, Liu RuiMing, Yang Jie: Small target detection using two-dimensional least mean square (TDLMS) filter based on neighborhood analysis. Int. J. Infrared Millim. Waves 29(2), 188–200 (2008)
Kim Sungho, Yang Yukyung, Lee Joohyoung, Park Yongchan: Small target detection utilizing robust methods of the human visual system for IRST. J. Infrared Millim. Terahertz Waves 30(9), 994–1011 (2009)
Shao Xiaopeng, Fan Hua, Lu Guangxu, Xu Jun: An improved infrared dim and small target detection algorithm based on the contrast mechanism of human visual system. Infrared Phys. Technol. 55(5), 403–408 (2012)
Deng He, Liu Jianguo, Chen Zhong: Infrared small target detection based on modified local entropy and EMD. Chin. Opt. Lett. 8(1), 24–28 (2010)
Wang Xin, Liu Lei, Tang Zhenmin: Infrared dim target detection based on fractal dimension and third-order characterization. Chin. Opt. Lett. 7(10), 931–933 (2009)
Deng He, Liu Jianguo: Infrared small target detection based on the self-information map. Infrared Phys. Technol. 54(2), 100–107 (2011)
Seo, Hae Jong, Milanfar, P.: Static and space-time visual saliency detection by self-resemblance. J. Vis. 9(12), 1–27 (2009)
Seo Hae Jong, Milanfar, P.: Visual saliency for automatic target detection, boundary detection, and image quality assessment. In: Proceedings of Acoustics Speech and Signal Processing (ICASSP), pp. 5578–5581. (2010)
Zhao Jufeng, Feng Huajun, Xu Zhihai, Li Qi, Peng Hai: Real-time automatic small target detection using saliency extraction and morphological theory. Opt. Laser Technol. 47, 268–277 (2013)
OTCBVS Benchmark Dataset Collection. http://www.vcipl.okstate.edu/otcbvs/bench/
Acknowledgments
This work is supported by the Defence Research and Development Organization (DRDO), New Delhi India, funding the project under the Directorate of Extramural Research & Intellectual Property Rights (ER & IPR) No. ERIP/ER/1103978/M/01/1347 dated July 28, 2011.
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Rajkumar, S., Chandra Mouli, P.V.S.S.R. (2015). Target Detection in Infrared Images Using Block-Based Approach. In: Rajsingh, E., Bhojan, A., Peter, J. (eds) Informatics and Communication Technologies for Societal Development. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1916-3_2
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DOI: https://doi.org/10.1007/978-81-322-1916-3_2
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