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Image stitching based on angle-consistent warping
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AI
DOI：10.1016/j.patcog.2021.107993.png)
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Abstract
En 中文
Many warping methods for image stitching have been proposed to construct panoramic image mo-saics free of artifacts. Existing methods heavily rely on coordinate correspondences between keypoints in stitching, which may not provide adequate constraints for alignment. In this paper, we discover and employ a new constraint & mdash; angle correspondences to address the above problem. The angle of a feature point represents the local directional structure of the point, which is an extension to its position and customarily ignored in image stitching. We propose to jointly consider the coordinates as well as the an -gles in keypoint correspondences. Such a strategy helps to generate a correct warping in the overlapping regions of the stitched image. In addition, we propose a novel constraint & mdash; mesh angle preservation to prevent undesired distortion in non-overlapping areas. Experiments in several challenging cases demon-strate that our method yields more accurate results with significantly less artifacts in comparison with state-of-the-art methods. (c) 2021 Elsevier Ltd. All rights reserved.
Keywords:
Image stitching
Image alignment
Homography estimation
Angle features