Reducing misregistration based on feature image mosaicing
Yi Ding, Tianjiang Wang, Xian Fu · 2012
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.