Journal of Guangxi Normal University(Natural Science Edition) ›› 2020, Vol. 38 ›› Issue (4): 42-53.doi: 10.16088/j.issn.1001-6600.2020.04.005

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An Image Stitching Method Based on Grid Warping and Cosine Function Weight

LI Jialiang, JIANG Pinqun*, XIA Haiying   

  1. College of Electronic Engineering, Guangxi Normal University, Guilin Guangxi 541004, China
  • Received:2019-07-24 Published:2020-07-13

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Abstract: An image stitching method based on the grid warping and cosine function weight is proposed to eliminate the ghost and chromatic gap in the stitched image. Firstly, the SIFT (scale-invariant feature transform) and RANSAC (random sample consensus algorithms) are used for the extraction and matching of feature points in the image to be stitched. Secondly, the GD (Gaussian distribution) model is used to remove the mismatched feature points. Then the cosine function is used as the weighting function of APAP (as-projective-as-possible image stitching) and global similarity transformation model. Finally, the cosine function weight is used to weight the warped image. The experimental results show that the stitching effect of this method is better than that of the classic algorithm, and the method can effectively eliminate the ghost and chromatic gap in the stitched image.

Key words: image stitching, image warping, scale-invariant feature transform, weight, ghosting

CLC Number: 

  • TP391
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