4.7 Article

Content-Preserving Image Stitching With Piecewise Rectangular Boundary Constraints

期刊

出版社

IEEE COMPUTER SOC
DOI: 10.1109/TVCG.2020.2965097

关键词

Content-preserving image stitching; panoramic image; rectangling; polygon boolean operations; piecewise rectangular boundary

资金

  1. National Natural Science Foundation of China [61602402]
  2. Zhejiang Province Public Welfare Technology Application Research [LGG19F020001]
  3. Victoria Early Career Research Excellence Award [224525]
  4. Royal Society [IES\R1\180126]

向作者/读者索取更多资源

This article proposes an approach to content-preserving image stitching with regular boundary constraints, aiming to generate a panoramic image with piecewise rectangular boundaries. By formulating image stitching with regular boundaries in a unified optimization framework, the method efficiently produces visually pleasing panoramas with regular boundaries and unnoticeable distortions.
This article proposes an approach to content-preserving image stitching with regular boundary constraints, which aims to stitch multiple images to generate a panoramic image with piecewise rectangular boundaries. Existing methods treat image stitching and rectangling as two separate steps, which may result in suboptimal results as the stitching process is not aware of the further warping needs for rectangling. We address these limitations by formulating image stitching with regular boundaries in a unified optimization framework. Starting from the initial stitching result produced by traditional warping-based optimization, we obtain the irregular boundary from the warped meshes by polygon Boolean operations which robustly handle arbitrary mesh compositions. By analyzing the irregular boundary, we construct a piecewise rectangular boundary. Based on this, we further incorporate line and regular boundary preservation constraints into the image stitching framework, and conduct iterative optimizations to obtain an optimal piecewise rectangular boundary. Thus we can make the boundary of the stitching result as close as possible to a rectangle, while reducing unwanted distortions. We further extend our method to video stitching, by integrating the temporal coherence into the optimization. Experiments show that our method efficiently produces visually pleasing panoramas with regular boundaries and unnoticeable distortions.

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