具有分流型抑制机制的视网膜细胞神经网络模型及其应用

视觉细胞之间存在的侧抑制机制能够对接收到的视觉信息进行选择性的提取。运用数学方法模拟视觉细胞之间存在的这种生理机制,提出了一种具有分流型抑制机制的视网膜细胞神经网络模型(SIRCNN),分析了该模型的稳定性,给出了等价电路图,并且基于此模型提出了一种边缘检测算法。将该算法应用于图像边缘检测中,试验结果表明,这种以生物视觉感知机理为基础的神经计算方法可有效地增强图像反差,检测图像边缘。由于细胞神经网络具有高速并行运算、便于硬件实现等特点,因此这种方法在图像实时处理中也具有很大的潜力和应用前景。

A Model of Shunting Inhibitory Retinal Cellular Neural Networks and Its Application

Through the mechanism called lateral inhibitory existing among the visual neurons, visual information can be selectively detected. Simulating this mechanism among visual cellars through a mathematical method, a shunting inhibitory retinal cellular neural networks(SIRCNN) model based on early vision is provided. The stability analysis of its dynamics and the equivalent circuit diagram are presented and a method of detecting edges based on this model is provided. From the test result, such a method based on the biological visual mechanisms can efficiently enhance and detect edges . Because the cellular neural networks are uniquely suitable for the high-speed parallel computation and easy to implement in hardware, this model has more potential in real-time image processing.