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Image Stitching with Efficient Brightness Fusion and Automatic Content Awareness

机译:图像拼接,具有高效亮度融合和自动内容意识

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Image Stitching, also be called photo stitching, is the process of combining multiple photographic images with overlapping fields of view to produce a segmented panorama or high-resolution image. Image stitching is challenging in two fields. First, the sequenced photos taken from various angles will have different brightness. This will certainly lead to a un-nature stitched result with no harmony of brightness. Second, ghosting artifact due to the moving objects is also a common problem and the elimination of it is not an easy task. This paper presents several novel techniques that make the process of addressing the two difficulties significantly less labor-intensive while also efficient. For the brightness problem, each input image is blended by several images with different brightness. For the ghosting problem, 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. 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.
机译:图像缝合,也称为照片缝合,是将多个摄影图像与重叠视野组合以产生分段全景或高分辨率图像的过程。图像拼接在两个领域有挑战性。首先,从各种角度拍摄的测序照片将具有不同的亮度。这肯定会导致无性缝合的结果,没有亮度的和谐。其次,由于移动物体引起的重影工件也是一个常见的问题,消除它不是一件容易的任务。本文介绍了几种新颖的技术,使得解决两种困难的过程明显减少劳动密集型,同时也有效。对于亮度问题,每个输入图像被几个具有不同亮度的图像混合。对于重影问题,我们提出了一种基于新的能量图的缝合线的直观技术,其基本上是梯度图的组合,其指示存在确定区域的吸引力的结构和突出地图的存在。缝合线可以容易地围绕移动物体或突出部位,基于人眼睛大多注意图像的突出特征。我们将方法的结果与4个最先进的图像拼接方法的结果进行比较,事实证明我们的方法优于消除重影伪影的4种方法。

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