Adaptive Target Detection Algorithm Using Gray Difference, Similarity and Adjacency 


Vol. 38,  No. 9, pp. 736-743, Sep.  2013


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  Abstract

In IRST(infrared search and track) system, the small target detection is very difficult because the IR(infrared) image have various clutter and sensor noise. The noise and clutter similar to the target intensity value produce many false alarms. In this paper. We propose the adaptive detection method which obtains optimal target detection using the image intensity information and the prior information of target. In order to enhance the target, we apply the human visual system. we determine the adaptive threshold value using image intensity and distance measure in target enhancement image. The experimental results indicate that the proposed method can efficiently extract target region in various IR images.

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  Cite this article

[IEEE Style]

E. Lee, E. Gu, H. Yoo, K. Park, "Adaptive Target Detection Algorithm Using Gray Difference, Similarity and Adjacency," The Journal of Korean Institute of Communications and Information Sciences, vol. 38, no. 9, pp. 736-743, 2013. DOI: .

[ACM Style]

Eun-young Lee, Eun-hye Gu, Hyun-jung Yoo, and Kil-houm Park. 2013. Adaptive Target Detection Algorithm Using Gray Difference, Similarity and Adjacency. The Journal of Korean Institute of Communications and Information Sciences, 38, 9, (2013), 736-743. DOI: .

[KICS Style]

Eun-young Lee, Eun-hye Gu, Hyun-jung Yoo, Kil-houm Park, "Adaptive Target Detection Algorithm Using Gray Difference, Similarity and Adjacency," The Journal of Korean Institute of Communications and Information Sciences, vol. 38, no. 9, pp. 736-743, 9. 2013.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880