Multi-Scale Blobs for Saliency Detection in Satellite Images

Saliency can be modeled as spatially localized and contrasted structures with higher blob density and higher blob evenness across scales in images. And it is likely to contain regions and objects of interest. So saliency detection is desired before further image processing and analysis. This paper presented an automatic and effective method for saliency detection in satellite images, based on multi-scale blob information. Firstly, multi-scale blob information were extracted from input images, to produce a blob map. Then, in the blob map, multi-level distance transform spread the blob information to the entire image, to generate a saliency map. Finally the saliency map was segmented to detect salient regions and to locate object centers. The experimental results illustrated its accuracy and stability for detecting salient regions (such as residential areas, parking lots and airplane docks) and for locating object centers in various satellite images