According to the characteristics of human visual system

a salient object detection method based on spectral residual and multi-resolution is proposed. We first compute the spectral residual of three features i.e. intensity

color and orientation under different scales to build a series of multi-resolution saliency maps

which can be combined through linear interpolation to generate three feature-saliency maps. Then we use k-means clustering for binary clustering and select the feature-saliency map with the largest distance between two centroids. Finally we apply dynamic threshold segmentation to get salient regions in an image. The experimental results on natural images show that the new algorithm is stable and practical

and we achieve satisfied results.