A Segmentation Approach Based on Grayscale Level Connectivity in IR Image
一种基于灰度级连通性的红外图像分割方法

A new segmentation approach is proposed based on grayscale level connectivity in IR image. In this connectivity, a grayscale image is connected if all level sets below a prespecified threshold are connected. First, the level-k characteristic opening using appropriate thresholding "keeps" only the regional maxima of image that are at or above level k, and flattens the rest. Second, level-k connected component decomposing based on target size can extract connected component that contain the objects of interest. The end step can segment target combining with simple thresholding. Experimental results in real IR images demonstrate the effectiveness and robustness of the proposed approach to enhance signal noise ratio, extract target and segment image.