A Hybrid Image Retargeting Approach via Combining Seam Carving and Grid Warping

Image retargeting is a critical technique for browsing images in diversified terminals. In this paper, we propose a hybrid image resizing approach by jointly using seam carving and warping. Firstly, based on the importance partition with the saliency map, we apply a weighted seam carving approach to make the seams distributed dispersedly in the important regions. Then we propose Content Aware Image Distance (CAID) to assess the deformation caused by removing seams. The weighted seam carving will stop with a fixed threshold to assure little visual image quality degradation. Finally, the grid based warping is utilized to achieve the final size with a global optimization model, since warping tends to avoid discontinuity artifacts of important region and typically make the distortion distribution of unimportant region more coherently. Experiments and comparison in the public RetargetMe dataset [1] with Dong [2], Energy-based deformation [3], Multi-operator [4], SeamCarving [5], Simple scaling operator, Shift-maps [6], Scale and Stretch [7], Streaming Video [8], Nonhomogeneous warping [9], show the superiority of the proposed approach.