Image retargeting based on spatially varying defocus blur map

Ali Karaali, C. Jung
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引用次数: 9

Abstract

This paper presents a new image retargeting method that explores blur information. Given the input image, we compute the blur map and estimate in-focus regions. For retargeting, we first try to crop image boundaries as much as possible (preserving in-focus regions). If cropping is not enough, we use seam carving exploring a novel blur-aware energy function that concentrates the seams in blurred regions of the image. Experimental results show that the proposed blur-aware retargeting scheme works better at preserving in-focus objects than other competitive retargeting algorithms.
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基于空间变化散焦模糊图的图像重定位
本文提出了一种利用模糊信息进行图像重定位的新方法。给定输入图像,我们计算模糊映射并估计焦点区域。为了重新定位,我们首先尝试尽可能地裁剪图像边界(保留焦点区域)。如果裁剪不够,我们使用接缝雕刻探索一种新的模糊感知能量函数,将图像模糊区域的接缝集中在一起。实验结果表明,所提出的模糊感知重定向方案比其他竞争性重定向算法能更好地保留焦点内的目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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