结合蚁群算法与二维直方图的红外图像分割

现有的图像分割算法存在着耗时量大，分割效果不佳等问题，不适用与红外系统领域的应用。针对上述问题，根据灰度级－梯度二维直方图的目标分割优势，通过与蚁群算法相结合，提出了一种结合蚁群算法与二维直方图的红外图像分割算法。通过在传统的灰度－梯度二维直方图进行引入边缘与噪声区域的相关量；通过将图像窗口化，并根据最佳分割阈值对蚁群的启发函数以及信息素更新进行重新定义，来实现红外目标的快速提取。实验结果表明，该算法分割后的红外目标边缘清晰，抗干扰能力较强，且运算速度也得到了有效提高。

Infrared image segmentation based on ant colony algorithm and two dimensional histogram

Existing image segmentation algorithm has the problems of large calculation amount and poor segmentation effect. Aiming at these problems,according to target segmentation characteristics of grayscale gradient two dimensional histogram,an infrared image segmentation algorithm based on ant colony algorithm and two dimensional histogram is proposed. The edges and noise correlation values are introduced into the traditional gray gradient two dimensional histogram. In order to extract infrared target rapidly,the image is divided into small windows,and the heuristic function and pheromone update function are redefined according to the optimal segmentation threshold. Experimental results show that the edge of infrared target is clear. The algorithm has a stronger anti jamming capability and faster computing speed.