Scale self-adaptive saliency detection of SAR image
Xie Huiji · Computer Engineering and Applications Journal · 2015
Human vision system can assign processing resource efficiently by saliency detection of different interesting objects in the scene. The saliency detection method based on the visual attention mechanism is employed to simplify the scene analysis and the target interpretation of remote sensing images, which economizes processing resources. On the foundation of visual attention mechanism, a scale self-adaptive saliency detection method of SAR image is proposed. The local complexity metric and self-dissimilarity metric of multiple scales are utilized to compute the saliency metric. Moreover, the way of saliency scale determination has been designed. The saliency map has been built by combining saliency metric with the saliency scale, which is the last step of saliency detection. Experimental results show that the proposed method can detect the saliency of SAR image effectively, and that the proposed method is more reliable for SAR image scene analysis than other state-of-the-art saliency detection methods.