De-ghosting for Image Stitching with Automatic Content-Awareness
De-ghosting for Image Stitching with Automatic Content-Awareness
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DOI：
10.1109/icpr.2010.541
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发表时间：
2010-10
期刊：
影响因子：
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通讯作者：
Yu Tang;Jungpil Shin
中科院分区：
文献类型：
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作者：
Yu Tang;Jungpil Shin
重影伪影是图像拼接领域的一个常见问题，消除重影伪影并不是一件容易的事情。在本文中，我们提出了一种直观的技术，根据缝合线的基础上，一种新的能量图，这基本上是一个组合的梯度图，表明存在的结构和突出的地图，这决定了一个区域的吸引力。我们认为，一个地区只有在结构性和吸引力方面才有意义。使用这种改进的能量图，拼接线可以很容易地绕过移动对象或显着部分的基础上的哲学，人眼主要注意到只有图像的显着特征。我们比较了我们的方法的结果与4个国家的最先进的图像拼接方法，它证明了我们的方法优于4种方法在消除重影伪影。
Ghosting artifact in the field of image stitching is a common problem and the elimination of it is not an easy task. In this paper, we propose an intuitive technique according to a stitching line based on a novel energy map which is essentially a combination of gradient map which indicates the presence of structures and prominence map which determines the attractiveness of a region. We consider a region is of significance only if it is both structural and attractive. Using this improved energy map, the stitching line can easily skirt around the moving objects or salient parts based on the philosophy that human eyes mostly notice only the salient features of an image. We compare result of our method to those of 4 state-of-the-art image stitching methods and it turns out that our method outperforms the 4 methods in removing ghosting artifacts.