复杂海空背景下弱小目标的快速自动检测

针对海面运动载体的可见光序列图像,结合复杂海空背景图像的特点,提出了一种不以检测海天线为前提的弱小目标检测方法.首先,修复图像中被高亮度噪声损毁的部分,如曝光区域或反光区域；接着,量化子图像的区域复杂度以及单元区域上下邻域的灰度差异,据此来判断海天线区域是否存在,若存在则预测海天线区域的位置,否则放弃后续处理；然后,采取Mean-shift分割算法中先滤波后聚类的策略,使用周围纹理抑制滤波来平滑海天线区域,并以像素点和点集为单位对平滑图像进行聚类；最后,将最大面积区域与其他区域分离来二值化图像,完成目标提取.试验证明,该方法能够很好地定位目标信息,单帧处理平均耗时为35 ms,具有准确性和实时性.

Fast detection of weak targets in complex sea-sky background

Without detection of the location of sea-sky line in advance,a feasible method combining with the characters of marine visible images and a complex sea-sky background was proposed to detect distant weak targets in the sequential images from a surface vehicle.Firstly,the images damaged by the noise such as exposures and reflections was mended by the border color of ruined range.Then,the complexity of sub-images and their neighborhood average gray difference were measured to predict the sea-sky region.If the sea-sky region was obtained,the location of the sea-sky should be predicted.Otherwise,the consequent process of images could be eliminated.The strategy of filtering and clustering in Mean-shift segmentation was adopted,in which the surround suppression filter was applied to smoothing the sea-sky region and the smoothed image was clustered by taking the pixels and points as units.Finally,the largest region was assumed to be the background and the rest was taken as target information.The experiment results prove that this method can locate the objects efficiently and the time cost is 35 ms/frame,which is robust and real-time.