Share Email Print
cover

Proceedings Paper

Small target detection using min-cut for non-balanced graph
Author(s): Airong Sun; Yihua Tan; Jinwen Tian
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Detection of infrared dim small target is an important task in many application fields such as automatic target detection, target search and tracking, and early warning. By combining the block-based background reconstruction and min-cut of non-balanced graph, a dim small target detection algorithm is presented. First, a background reconstruction based on a new modeling is presented. Secondly, the background is suppressed though subtracting the reconstructed image from the original image. Lastly, further segmentation using min-cut for non-balanced graph to the background suppressed image is proposed in order to obtain the binary image containing target. The optimal segmentation threshold is selected by heuristic search based on the optimal min-cut. Experimental results show that the proposed method can suppress background noise and clutter effectively and detect infrared small target accurately.

Paper Details

Date Published: 26 October 2013
PDF: 8 pages
Proc. SPIE 8918, MIPPR 2013: Automatic Target Recognition and Navigation, 89181C (26 October 2013); doi: 10.1117/12.2031403
Show Author Affiliations
Airong Sun, Wuhan Institute of Technology (China)
Huazhong Univ. of Science and Technology (China)
Yihua Tan, Huazhong Univ. of Science and Technology (China)
Jinwen Tian, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 8918:
MIPPR 2013: Automatic Target Recognition and Navigation
Tianxu Zhang; Nong Sang, Editor(s)

© SPIE. Terms of Use
Back to Top