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Reducing misregistration based on feature image mosaicing

机译:基于特征图像拼接减少误解

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Image mosaicing has been collecting widespread attention because it can automatically construct a panoramic image from multiple images. Among previous methods, homograph-based methods are the most accurate in the geometric sense. This is because these methods use planar projective transformation, which considers perspective effects as a geometric transformation model between images. We propose an automatic image mosaicing method which can construct a panoramic image from a collection of digital still images. These methods, however, have a problem of misregistration in the case of general scenes with arbitrary camera motion. Our method can reduce this misregistration by using geometric constraints called trilinearity. Experiments using real images confirm the effectiveness of our method.
机译:图像镶嵌一直在收集广泛的注意,因为它可以自动构建来自多个图像的全景图像。 在以前的方法中,基于同类的方法是几何意义上最准确的方法。 这是因为这些方法使用平面投射转换,这将透视效应视为图像之间的几何变换模型。 我们提出了一种自动图像镶嵌方法,可以从一系列数字静止图像构建全景图像。 然而,这些方法在具有任意摄像机运动的一般场景的情况下存在误解。 我们的方法可以通过使用称为TrileineARITY的几何约束来减少这种误印。 使用真实图像的实验证实了我们方法的有效性。

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