Quantum image stitching based on SIFT algorithm with dynamic threshold and global information

Zetian TANG; Zhao DING; Ruimin ZENG; Minzhe ZHONG; Dengwei ZHU; Yuhao WANG; Yang WANG; Chen YANG

doi:10.3969/j.issn.1007-5461.2020.01.004

Journals >Chinese Journal of Quantum Electronics >Volume 37 >Issue 1 >Page 22 > Article

Chinese Journal of Quantum Electronics
Vol. 37, Issue 1, 22 (2020)

Quantum image stitching based on SIFT algorithm with dynamic threshold and global information

Zetian TANG^1、2、*, Zhao DING^1、2, Ruimin ZENG^1、2, Minzhe ZHONG^1、2, Dengwei ZHU^1、2, Yuhao WANG^1、2, Yang WANG^1、2, and Chen YANG^1、2、3

Author Affiliations

¹[in Chinese]

²[in Chinese]

³[in Chinese]

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DOI: 10.3969/j.issn.1007-5461.2020.01.004 Cite this Article

TANG Zetian, DING Zhao, ZENG Ruimin, ZHONG Minzhe, ZHU Dengwei, WANG Yuhao, WANG Yang, YANG Chen. Quantum image stitching based on SIFT algorithm with dynamic threshold and global information[J]. Chinese Journal of Quantum Electronics, 2020, 37(1): 22 Copy Citation Text

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References

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[3] Ghosh D, Kaabouch N. A survey on image mosaicing techniques [J]. Journal of Visual Communication and Image Representation, 2016, 34(C): 1-11.

[4] Zhang K, Li X Z, Zhang J X. A robust point-matching algorithm for remote sensing image registration [J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(2): 469-473.

[5] Wu Y, Ma W P, Gong M G, et al. A novel point-matching algorithm based on fast sample consensus for image registration [J]. IEEE Geoscience and Remote Sensing Letters, 2015, 12(1): 43-47.

[7] Lowe D G. Distinctive image features from scale-invariant keypoints [J]. International Journal of Computer Vision, 2004, 60(2): 91-110.

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