Image Stitching Method for Improvement of Artifact

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Image Stitching Method for Improvement of Artifact

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[1]YAO Li,DU Junkang,LI Changshun.Image Stitching Method for Improvement of Artifact[J].Journal of Zhengzhou University (Engineering Science),2021,42(01):35-41.[doi:10.13705/j.issn.1671-6833.2021.01.006]

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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 42卷 Number of periods: 2021 01 Page number: 35-41 Column: Public date: 2021-03-14

Title:: Image Stitching Method for Improvement of Artifact

Author(s):: YAO Li; DU Junkang; LI Changshun; School of Computer Science and Engineering, Southeast University, Nanjing 211102, China

Keywords:: image stitching; artifact; grid optimization; image registration

CLC:: TP37

DOI:: 10.13705/j.issn.1671-6833.2021.01.006

Abstract:: This paper focused on solving the problem of artifact in image mosaic technology, and proposed a whole set of mosaic scheme to solve the problem. Image stitching method was divided into two stages: image registration stage and image fusion stage. In the stage of image registration, in this paper, an image registration method based on grid optimization was proposed. By using the feature extraction algorithm combining point feature and line feature, the quantity and quality of features could be improved. At the same time, a prior screening method of RANSAC feature point pairs was proposed, which could eliminate mismatching point pairs and improve the speed of model calculation. In order to further improve the alignment effect and optimize the artifacts, a number of image alignment constraints were proposed. Finally, the cylinder projection model was used to project the image pairs to the same plane. In the stage of image fusion, a seam-line detection algorithm based on the enhancement of the details of the overlapping areas of the image was used to optimize the stitching effect in the multi-focus scene. The gradual image fusion algorithm was used to fuse the projection image of the same plane, and a wide field of vision high-resolution image mosaic result was obtained. The existing splicing methods were compared with the method in this paper. The results showed that the methods in this paper maintained the PSNR value verified in multiple scenarios in the range of 35-40 dB with low distortion, which could deal with the problem of artifacts better, and could have better performance in image stitching quality.

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Last Update: 2021-03-15