Saliency guided adaptive image abstraction

We have developed a novel method for image abstraction which preserves more details present in the salient regions and removes details present in the non-salient regions from the given image of a natural scene. We define a region to be salient based on the saliency measure estimated in the region. We propose to preserve details in salient regions by dividing them into smaller groups of pixels and remove details from non-salient regions by dividing them in larger group of pixels. We achieve this kind of grouping by guiding an over-segmentation algorithm with spatially varying block size depending on the saliency measure. The adaptive image abstraction goal is finally achieved using a novel brush called point spread brush which is used to reproduce the action of brush with a varying spatial spread.