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Optimal-Scaling-Factor Assignment for Patch-wise Image Retargeting
Sept.-Oct. 2013 (vol. 33 no. 5)
pp. 68-78
Yun Liang, South China Agricultural University
Yong-Jin Liu, Tsinghua University
Xiao-Nan Luo, Sun Yat-sen University
Lexing Xie, Australian National University
Xiaolan Fu, Chinese Academy of Sciences
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.
Index Terms:
Image edge detection,Object recognition,Electronic mail,Targeting,Human factors,Psychology,computer graphics,image retargeting,patch-wise scaling factor assignment
Citation:
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
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