6 August 2009 IR image signature of target detection based on the morphology filter with self-adaptive optimized genetic algorithms
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Abstract
It is utilized the morphology filter and self-adaptive genetic algorithm to present the morphology filter with selfoptimized genetic algorithms (MFGA) for detecting IR image signature of the target. According to training the structuring element from original image data, some constraint conditions such as the prior knowledge and statistics laws , we summarize a judgment rule on finding out the best of structuring elements. As two special applications about IR image signature of the detections, one is detected solid thruster plume IR image and the other is weak-small infrared target under complex background. Compared the experimental results of the MFGA with those of the morphology filter (MF), we find that the MFGA has high convergence speed, greatly enhanced the Signal Noise ratio of target detection and effectively detecting target from complex background. And the experimental results and methods have a great significance in aerial forecasting and space defense.
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Ming-jun Wang, Ming-jun Wang, Zhen-sen Wu, Zhen-sen Wu, Ying-le Li, Ying-le Li, Yun-qiang Wang, Yun-qiang Wang, } "IR image signature of target detection based on the morphology filter with self-adaptive optimized genetic algorithms", Proc. SPIE 7383, International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Infrared Imaging and Applications, 73832E (6 August 2009); doi: 10.1117/12.834095; https://doi.org/10.1117/12.834095
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