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Issue No.05 - Sept.-Oct. (2013 vol.33)
pp: 68-78
Yun Liang , South China Agric. Univ., China
Yong-Jin Liu , Tsinghua Univ., Beijing, China
Xiao-Nan Luo , SunYat-sen Univ., China
Lexing Xie , Australian Nat. Univ., Canberra, ACT, Australia
Xiaolan Fu , Chinese Acad. of Sci., Beijing, China
Image retargeting adjusts images to arbitrary sizes such that they can be viewed on different displays. Content-aware image retargeting has been receiving increased attention. In particular, researchers have improved a patch-wise scaling method for image retargeting at the object level. The scaling partitions the image into rectangular patches of adaptive sizes, which are comparable to the sizes of the salient objects in the image. This partitioning is based on a visual-saliency map; accordingly, the method labels the patches as important or unimportant. Then, the method scales the important patches as uniformly as possible and stretches or squeezes the unimportant patches to fit the target size. A patch-based image-similarity measure finds the optimal set of scaling factors. In experiments, the improved method performed well for three image types: lines and edges, foreground objects, and geometric structures.
Image edge detection, Object recognition, Electronic mail, Targeting, Human factors, Psychology,computer graphics, image retargeting, patch-wise scaling factor assignment
Yun Liang, Yong-Jin Liu, Xiao-Nan Luo, Lexing Xie, Xiaolan Fu, "Optimal-Scaling-Factor Assignment for Patch-wise Image Retargeting", IEEE Computer Graphics and Applications, vol.33, no. 5, pp. 68-78, Sept.-Oct. 2013, doi:10.1109/MCG.2012.123
1. Y. Liang , Z. Su , and X.-N. Luo , “Patch-wise Scaling Method for Content-Aware Image Resizing,” Signal Processing, vol. 92, no. 5, 2012, pp. 1243-1257.
2. C. Barnes et al., “PatchMatch: A Randomized Corre-spondence Algorithm for Structural Image Editing,” ACM Trans. Graphics, vol. 28, no. 3, 2009, article 24.
3. S. Avidan and A. Shamir , “Seam Carving for Content-Aware Image Resizing,” ACM Trans. Graphics, vol. 26, no. 3, 2007, article 10.
4. J. Harel , C. Koch , and P. Perona , “Graph-Based Visual Saliency,” Advances in Neural Information Processing Systems 19, MIT Press, 2007, pp. 545-552.
5. Y.-S. Wang et al., “Optimized Scale-and-Stretch for Image Resizing,” Proc. Siggraph Asia ’08, ACM, 2008, article 118.
6. M. Rubinstein , A. Shamir , and S. Avidan , “Multi-operator Media Retargeting,” ACM Trans. Graphics, vol. 28, no. 3, 2009, article 23.
7. D. Simakov et al., “Summarizing Visual Data Using Bidirectional Similarity,” Proc. 2008 IEEE Conf. Computer Vision and Pattern Recognition (CVPR 08), 2008, IEEE.
8. W. Dong et al., “Optimized Image Resizing Using Seam Carving and Scaling,” Proc. Siggraph Asia ’09, ACM, 2009, article 125.
9. Z. Wang et al., “Image Quality Assessment: From Error Visibility to Structural Similarity,” IEEE Trans. Image Processing, vol. 13, no. 4, 2004, pp. 600-612.
10. M. Rubinstein et al., “A Comparative Study of Image Retargeting,” Proc. Siggraph Asia ’10, ACM, 2010, article 160.
11. Y. Liu et al., “Image Retargeting Quality Assessment,” Computer Graphics Forum, vol. 30, no. 2, 2011, pp. 583-592.
12. D. Panozzo , O. Weber , and O. Sorkine , “Robust Image Retargeting via Axis-Aligned Deformation,” Computer Graphics Forum, vol. 31, no. 2, 2012, pp. 229-236.
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