Optimal-Scaling-Factor Assignment for Patch-wise Image Retargeting
Optimal-Scaling-Factor Assignment for Patch-wise Image Retargeting
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DOI：
10.1109/mcg.2012.123
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发表时间：
2013-09
影响因子：
1.8
通讯作者：
Yun Liang;Yong-Jin Liu;Xiaonan Luo;Lexing Xie;Xiaolan Fu
中科院分区：
文献类型：
--
作者：
Yun Liang;Yong-Jin Liu;Xiaonan Luo;Lexing Xie;Xiaolan Fu
图像重定向将图像调整为任意尺寸，以便可以在不同的显示器上查看。内容感知图像重定向越来越受到关注。特别是，研究人员改进了用于对象级别图像重定向的逐块缩放方法。缩放将图像划分为自适应尺寸的矩形块，其与图像中显着对象的尺寸相当。这种划分是基于视觉显着性图；因此，该方法将补丁标记为重要或不重要。然后，该方法尽可能均匀地缩放重要的补丁，并拉伸或挤压不重要的补丁以适应目标大小。基于补丁的图像相似性度量可以找到最佳的缩放因子集。在实验中，改进的方法对于线条和边缘、前景物体和几何结构三种图像类型表现良好。
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.