Fusing Warping, Cropping, and Scaling for Optimal Image Thumbnail Generation

Abstract

Image retargeting, as a content aware technique, is regarded as a logical tool for generating image thumbnails. However, the enormous difference between the size of source and target usually hinders single retargeting method from obtaining satisfactory results. In this paper, an unified framework is proposed to fuse three popular retargeting strategies, i.e. warping, cropping, and scaling, for thumbnail generation. Complementing each other, three retargeting strategies work together efficiently. Firstly, cropping selectively discards the unimportant regions in order to free up more space for displaying important content aesthetically. Next, warping helps to incorporate as much as possible visual information into thumbnails by rearranging important content more compactly through non-uniform deformation. Finally, scaling retrains the important content at an optimal size rather than undergoing an improper shrinkage. In our solution, warping, cropping and scaling are encoded as three energy terms of the objective function respectively, which can be solved efficiently by numerical optimization. Both qualitative and quantitative comparison results demonstrate that the proposed method achieves an excellent trade-off among smoothness, completeness and distinguishableness in thumbnail generation. Through these results, our method shows obvious superiority over state-of-the-art techniques.