基于脉冲耦合神经网络的空中扩展目标检测

 对单位链接脉冲耦合神经网络模型中的线性调制、动态阈值衰减方式及步长、迭代次数控制等关键环节进行了改进，进一步简化了网络模型，使其更适合于图像处理。并针对低对比度、背景连续变化环境下的空中扩展目标检测问题，应用反色处理，并采用最大直线轮廓点数方法，确定其最佳迭代次数和分割结果，实现目标的自动检测。仿真实验结果表明，该方法能清晰完整地保留目标轮廓，有效检测出复杂背景下的空中扩展目标。

Aerial extended target detection based on unit-linking pulse coupled neural networks

A novel method of aerial extended target detection based on pulse coupled neural network(PCNN) is presented.Some key techniques are improved and network model is simplified,which are more suitable for image processing,such as linear modulation,linear attenuation of dynamic threshold and step selection,and iteration time control.Meanwhile,maximum line contour point number and color negative are adopted to determine the optimal iteration times and the optimal segmented results for targets with low contrast and continuously varying background.The experimental results show that the proposed method can maintain perfect and distinct targets contour and detect aerial extended targets against complex background.