图像拼接(image stitching)是指将两张或更多的有重叠部分的影像,拼接成一张全景图或是高分辨率影像的技术。图像拼接有两大步骤:图像配准和图像融合

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作者简介: 艾海舟,清华大学计算机系教授,目前主要从事与人脸人体相关的计算机视觉方面的研究,在人脸及人体图像理解领域提出了一系列性能优越的算法,具有重要的学术价值和明显的应用价值。发表论文80余篇,授权国际专利1项,国际专利申请4项。

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最新论文

We propose a novel method for large-scale image stitching that is robust against repetitive patterns and featureless regions in the imagery. In such cases, state-of-the-art image stitching methods easily produce image alignment artifacts, since they may produce false pairwise image registrations that are in conflict within the global connectivity graph. Our method augments the current methods by collecting all the plausible pairwise image registration candidates, among which globally consistent candidates are chosen. This enables the stitching process to determine the correct pairwise registrations by utilizing all the available information from the whole imagery, such as unambiguous registrations outside the repeating pattern and featureless regions. We formalize the method as a weighted multigraph whose nodes represent the individual image transformations from the composite image, and whose sets of multiple edges between two nodes represent all the plausible transformations between the pixel coordinates of the two images. The edge weights represent the plausibility of the transformations. The image transformations and the edge weights are solved from a non-linear minimization problem with linear constraints, for which a projection method is used. As an example, we apply the method in a large-scale scanning application where the transformations are primarily translations with only slight rotation and scaling component. Despite these simplifications, the state-of-the-art methods do not produce adequate results in such applications, since the image overlap is small, which can be featureless or repetitive, and misalignment artifacts and their concealment are unacceptable.

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