Local facet approximation for image stitching

Jing Li; Shiming Lai; Yu Liu; Zhengming Wang; Maojun Zhang

doi:10.1117/1.JEI.27.1.013011

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26 January 2018 Local facet approximation for image stitching

Jing Li, Shiming Lai, Yu Liu, Zhengming Wang, Maojun Zhang

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J. of Electronic Imaging, 27(1), 013011 (2018). https://doi.org/10.1117/1.JEI.27.1.013011

Abstract

Image stitching aims at eliminating multiview parallax and generating a seamless panorama given a set of input images. This paper proposes a local adaptive stitching method, which could achieve both accurate and robust image alignments across the whole panorama. A transformation estimation model is introduced by approximating the scene as a combination of neighboring facets. Then, the local adaptive stitching field is constructed using a series of linear systems of the facet parameters, which enables the parallax handling in three-dimensional space. We also provide a concise but effective global projectivity preserving technique that smoothly varies the transformations from local adaptive to global planar. The proposed model is capable of stitching both normal images and fisheye images. The efficiency of our method is quantitatively demonstrated in the comparative experiments on several challenging cases.

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Jing Li, Shiming Lai, Yu Liu, Zhengming Wang, and Maojun Zhang "Local facet approximation for image stitching," Journal of Electronic Imaging 27(1), 013011 (26 January 2018). https://doi.org/10.1117/1.JEI.27.1.013011

Received: 28 July 2017; Accepted: 3 January 2018; Published: 26 January 2018

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