针对SAR图像中显著性目标检测问题,提出一种基于多尺度自卷积方差显著性的自适应检测算法.该算法在对SAR图像多尺度自卷积运算基础上,通过计算MSAV得到方差显著图.设计了一种白适应阈值检测器,完成SAR图像中显著性目标的检测.实验结果表明,在复杂背景环境下,所提算法能有效检测出与人类视觉较为一致的显著性目标.
To detect salient objects in SAR image, an adaptive detection method is proposed based on multi-scale auto-convolution variance (MSAV) saliency. With multi-scale auto-convolution operation in SAR image and by calculating MSAV, a variance saliency map is obtained. An auto-threshold-selecting detector is constructed and salient object detection from the SAR image is achieved. Experimental results show that, by applying the proposed algorithm to a complex scene, salient objects consistent with human visual sense can be effectively detected.