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根据元胞神经网络图像处理模型,提出了一种海空光电目标的检测方法。与传统的方法不同,元胞神经网络是一种新的图像处理模式。它把图像看成一个动力系统,如果设置合适的模板参数与初始条件,就能达到特定的图像处理功能。首先对图像进行预处理和直方图修正,然后利用CNN进行分割,最后检测出目标。通过仿真实例,结果表明,该方法能较好地检测出海空目标,准确率较高,并且满足实时处理的要求,具有一定的军事应用价值。
According to the cellular neural network image processing model, a detection method of sea-sky photoelectric target is proposed. Different from the traditional method, Cellular Neural Network is a new image processing mode. It regards the image as a dynamic system, and if we set the appropriate template parameters and initial conditions, we can achieve the specific image processing function. First, the image preprocessing and histogram correction, and then use CNN segmentation, and finally detect the target. The simulation results show that the proposed method can detect the target of the sea and air well with high accuracy and meet the requirements of real-time processing, which has certain military application value.