Target attribute-based false alarm rejection in small infrared target detection

Sungho Kim

doi:10.1117/12.973766

8 November 2012 Target attribute-based false alarm rejection in small infrared target detection

Sungho Kim

Proceedings Volume 8537, Image and Signal Processing for Remote Sensing XVIII; 85370G (2012) https://doi.org/10.1117/12.973766
Event: SPIE Remote Sensing, 2012, Edinburgh, United Kingdom

Abstract

Infrared search and track is an important research area in military applications. Although there are a lot of works on small infrared target detection methods, we cannot apply them in real field due to high false alarm rate caused by clutters. This paper presents a novel target attribute extraction and machine learning-based target discrimination method. Eight kinds of target features are extracted and analyzed statistically. Learning-based classifiers such as SVM and Adaboost are developed and compared with conventional classifiers for real infrared images. In addition, the generalization capability is also inspected for various infrared clutters.

Citation Download Citation

Sungho Kim "Target attribute-based false alarm rejection in small infrared target detection", Proc. SPIE 8537, Image and Signal Processing for Remote Sensing XVIII, 85370G (8 November 2012); https://doi.org/10.1117/12.973766

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