Modify model for infrared dim target detection

Ruo-lan Hu; Xiao Zhou; Guo-hua Zhang; Gui-lin Zhang

doi:10.1117/12.901025

8 September 2011 Modify model for infrared dim target detection

Ruo-lan Hu, Xiao Zhou, Guo-hua Zhang, Gui-lin Zhang

Proceedings Volume 8193, International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications; 819346 (2011) https://doi.org/10.1117/12.901025
Event: International Symposium on Photoelectronic Detection and Imaging 2011, 2011, Beijing, China

Abstract

More and more infrared imaging systems were applied in military and civil fields due to the ability of detecting in night. Performance of detecting dim target is one important index for infrared imaging system. But it is difficult to detect dim target from infrared image due to weak in luminous and small in sizes. An important approach based on background suppression was used in many applications for it was effective in most applications and computed easily and quickly. But the performance of target detection were descended with many numbers of false alarms when there exists noise pixels in infrared image. In order to resolve the problem induced by noise pixels, in this paper a modify detection model was proposed. Modify detection model use two step filter processes to suppress noise and estimate background image. After selecting the first filter operator, a detection system base on modify detection model was realized. Experiment results show that modify detection model improve target detection ratio and reduce the numbers of false alarm on noisy infrared images.

Citation Download Citation

Ruo-lan Hu, Xiao Zhou, Guo-hua Zhang, and Gui-lin Zhang "Modify model for infrared dim target detection", Proc. SPIE 8193, International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, 819346 (8 September 2011); https://doi.org/10.1117/12.901025

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KEYWORDS

Target detection

Infrared imaging

Infrared radiation

Image filtering

Infrared detectors

Image segmentation

Digital filtering

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