Optimal-scaling-factor assignment for patch-wise image retargeting

Yun Liang, Yong Jin Liu, Xiao Nan Luo, Lexing Xie, Xiaolan Fu

    Research output: Contribution to journalArticlepeer-review

    10 Citations (Scopus)

    Abstract

    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.

    Original languageEnglish
    Article number6341003
    Pages (from-to)68-78
    Number of pages11
    JournalIEEE Computer Graphics and Applications
    Volume33
    Issue number5
    DOIs
    Publication statusPublished - 2013

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