Straightforward image resizing operators without considering image contents(e.g.,uniform scaling)cannot usually produce satisfactory results,while content-aware image retargeting aims to arbitrarily change image size ...Straightforward image resizing operators without considering image contents(e.g.,uniform scaling)cannot usually produce satisfactory results,while content-aware image retargeting aims to arbitrarily change image size while preserving visually prominent features.In this paper,a cluster-based saliency-guided seam carving algorithm for content-aware image retargeting is proposed.To cope with the main drawback of the original seam carving algorithm relying on only gradient-based image importance map,we integrate a gradient-based map and a cluster-based saliency map to generate a more reliable importance map,resulting in better single image retargeting results.Experimental results have demonstrated the efficacy of the proposed algorithm.展开更多
基金supported by“MOST”under Grants No.105-2628-E-224-001-MY3 and No.103-2221-E-224-034-MY2
文摘Straightforward image resizing operators without considering image contents(e.g.,uniform scaling)cannot usually produce satisfactory results,while content-aware image retargeting aims to arbitrarily change image size while preserving visually prominent features.In this paper,a cluster-based saliency-guided seam carving algorithm for content-aware image retargeting is proposed.To cope with the main drawback of the original seam carving algorithm relying on only gradient-based image importance map,we integrate a gradient-based map and a cluster-based saliency map to generate a more reliable importance map,resulting in better single image retargeting results.Experimental results have demonstrated the efficacy of the proposed algorithm.
