基于融合显著图和高效子窗口搜索的红外目标分割

为了快速精确地分割红外图像目标，提出一种基于融合显著图和高效子窗口搜索的红外目标分割方法.在获取图像超像素的基础上，提取每个区域增强的Sigma特征，并考虑邻域对比度、背景对比度、空间距离和区域大小的影响，构建局部显著图，接着利用全局核密度估计构建全局显著图，然后融合局部和全局显著图实现图像显著性检测，最后应用高效子窗口搜索方法检测和筛选目标，实现红外目标分割.实验结果表明，新方法的显著图结果目标区域一致高亮且边缘清晰，背景杂波抑制效果好，可实现快速精确的目标分割.

Target Segmentation of Infrared Image Using Fused Saliency Map and Efficient Subwindow Search

In order to segment infrared target fast and precisely, a segmentation method using fused saliency map and efficient subwindow search is proposed. Firstly, based on image superpixels, the enhanced sigma feature of every region is extracted, and at the same time considering the influence of neighbor contrast, background contrast, spatial distance and region's size, the local saliency map is constructed. Next, the global saliency map is obtained by global kernel density estimation. Then, the saliency detection result of infrared image is obtained by fusing the local and global saliency maps. Finally, the efficient subwindow search method is used to detect and segment the target. Experimental results show that the saliency map of the proposed method has complete target feature, obvious edges and good background suppression, and that the algorithm can segment the infrared target fast and precisely.