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Small Target Detection Algorithm Based on Average Absolute Difference Maximum and Background Forecast

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Abstract

Detecting small targets in clutter scene and low SNR (Signal Noise Ratio) is an important and challenging problem in infrared (IR) images. In order to solve this problem, we should do works from two sides: enhancing targets and suppressing background. Firstly, in this paper, the system utilizes the average absolute difference maximum (AADM) as the dissimilarity measurement between targets and background region to enhance targets. Secondly, it uses a predictor to suppress the background clutter. Finally, our approach extracts the interested small target with segment threshold. Experimental results show that the algorithm proposed has better performance with respect to probability of detection and less computation complexity. It is an effective small infrared target detection algorithm against complex background.

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Acknowledgment

This work has been supported by the National Defense Science Foundation of P.R. China (51401020201JW0521).

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Authors and Affiliations

  1. Institute of Pattern Recognition & Artificial Intelligence, Huazhong University of Science and Technology, Luoyu Road 1037, Wuhan, 430074, People’s Republic of China

    Zhenxue Chen, Guoyou Wang & Jianguo Liu

  2. College of Science, Wuhan University of Science and Technology, Wuhan, 430081, People’s Republic of China

    Chengyun Liu

Authors
  1. Zhenxue Chen
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  2. Guoyou Wang
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  3. Jianguo Liu
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  4. Chengyun Liu
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Correspondence to Zhenxue Chen.

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Chen, Z., Wang, G., Liu, J. et al. Small Target Detection Algorithm Based on Average Absolute Difference Maximum and Background Forecast. Int J Infrared Milli Waves 28, 87–97 (2007). https://doi.org/10.1007/s10762-006-9164-x

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  • DOI: https://doi.org/10.1007/s10762-006-9164-x

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