邵振峰, 李德仁, 朱先强. 利用改进的遗传算法对红外影像自适应目标进行检测[J]. 武汉大学学报 ( 信息科学版), 2011, 36(5): 535-539.
引用本文: 邵振峰, 李德仁, 朱先强. 利用改进的遗传算法对红外影像自适应目标进行检测[J]. 武汉大学学报 ( 信息科学版), 2011, 36(5): 535-539.
SHAO Zhenfeng, LIDeren, ZHU Xianqiang. Adaptive Target Detection Based on Improved Genetic Algorithm in Infrared Images[J]. Geomatics and Information Science of Wuhan University, 2011, 36(5): 535-539.
Citation: SHAO Zhenfeng, LIDeren, ZHU Xianqiang. Adaptive Target Detection Based on Improved Genetic Algorithm in Infrared Images[J]. Geomatics and Information Science of Wuhan University, 2011, 36(5): 535-539.

利用改进的遗传算法对红外影像自适应目标进行检测

Adaptive Target Detection Based on Improved Genetic Algorithm in Infrared Images

  • 摘要: 针对红外影像背景复杂、噪声污染严重的特点,提出了一种基于训练样本的形态学背景估计方法,并将其应用于天空背景下的小目标检测及复杂自然背景下的人物目标检测实验。实验结果表明,改进的遗传算法不仅有效地改善了其过早收敛的缺陷,还增强了算法的局部探索能力,可消除复杂自然背景的影响,并可以有效地抑制椒盐噪声,检测结果的查准率和虚警率均有很大改进。

     

    Abstract: A novel background estimation algorithm is proposed for target detection in infrared images,and we employ it in sky background small target detection and complex ground background human target detection application.The experimental results show that with the assistant of the trained structure elements and morphology target detection method,the complex background can be removed properly;the noise also can be effectively restrained,and the algorithm's accuracy and false positives both are improved.

     

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