Salient region detection in remote sensing images based on color information content
Libao Zhang, Shuang Wang, Xuewei Li · 2015
Accurate and anti-noise detection of salient regions is a hotspot of remote sensing image analysis. In this paper, we introduce a new salient region detection model for residential areas in high-spatial-resolution remote sensing images, which is called Color Information Content model (CIC), applying color information content and outputting full resolution saliency maps. First, one-dimensional (1D) histograms of different color channels are constructed based on intensities. Second, the information content of intensities is computed on the 1D histograms and an information mapping is used to construct information maps which reflect information content of each colour channel. Finally, to establish saliency map, intensities of different color channels are fused by saliency scores based on information maps. Experimental results show that compared with existing models, our model not only gets accurate results effectively, but also has good noise immunity.