基于CNN-PDE偏差异质扩散预处理的红外图像分水岭分割

Infrared image watershed segmentation based on the preprocess by CNN-PDE bias-anisotropic diffusion filter

为了抑止采用分水岭方法分割红外图像时的过分割现象,首先利用细胞神经网络高效求解偏微分方程的能力,实现了可调偏差异质扩散滤波器并用其对图像作预处理.为了消除噪声残留,引入了平滑系数与限制强度系数对梯度图作阈值化处理.实际红外图像的分水岭分割结果显示,所提出的预处理方法能够有效抑止过分割现象.

The watershed algorithm leads to over-segment when it was used to segment an infrared image. An adjustable bias-anisotropic diffusion filter based on CNN-PDE for smoothing an infrared image was studied. In order to remove the residual noise which can not be smoothed by filter, the smoothing coefficient and constrain coefficient were used to threshold the gradient image. The result of watershed segmentation of a practical infrared image shows the presented method can restrain over-segmentation effectively.