Detecting dim point target in infrared image sequences using probabilistic neural network

Haixin Chen; Zhenkang Shen; Huihuang Chen

doi:10.1117/12.169438

1 March 1994 Detecting dim point targets in infrared image sequences using probabilistic neural networks

Haixin Chen, Zhenkang Shen, Huihuang Chen

Proceedings Volume 2237, Optical Pattern Recognition V; (1994) https://doi.org/10.1117/12.169438
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

In spite of many advances of IR imaging technology that have been achieved, the detection of dim point targets from IR clutter backgrounds still remains a key problem in real-time IR systems. We present a new detection scheme based on a linear detector and an improved probabilistic neural network classifier for small SNR, moving point targets detection in strong IR noise and clutter backgrounds. Computer simulation was conducted and simulation results confirmed the validity of the detection scheme.

Citation Download Citation

Haixin Chen, Zhenkang Shen, and Huihuang Chen "Detecting dim point targets in infrared image sequences using probabilistic neural networks", Proc. SPIE 2237, Optical Pattern Recognition V, (1 March 1994); https://doi.org/10.1117/12.169438

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