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Research on threshold segmentation algorithm and its application on infrared small target detection algorithm

机译:阈值分割算法研究及其对红外小目标检测算法的应用

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For infrared dim target detection, proposed an improved Otsu algorithm, advantages in the search for the optimal solution using genetic algorithms, use class variance between the image pixels as a judgment function, realized the improved algorithm, reached the class variance detection threshold segmentation algorithm improvements. Infrared image processing by real infrared video sampling, the proposed algorithm with traditional the Otsu algorithm simulation comparison, experimental results show that the proposed algorithm guaranteed under the premise of the detection accuracy of the segmentation algorithm, to the improvement of the performance of real-time processing of traditional algorithms, excellent algorithm program with a value of engineering practice.
机译:对于红外暗淡目标检测,提出了一种改进的OTSU算法,在搜索最佳解决方案的优点,使用遗传算法,在图像像素之间使用类方差作为判断功能,实现了改进的算法,达到了类方差检测阈值分割算法的改进。红外图像处理通过真正的红外视频采样,所提出的算法与传统的OTSU算法模拟比较,实验结果表明,所提出的算法在分割算法检测准确性的前提下,提高了实时性能的预测传统算法的处理,具有工程实践价值的优秀算法节目。

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