Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications

No-Reference Image Mosaicing Method Based on the Generalized Evidence Theory

Authors
Yi She, Junjie Wu, Xin Chen, Guoqing Ding, Lihua Lei, Xiaoyu Cai, Jiasi Wei
Corresponding Author
Yi She
Available Online January 2017.
DOI
10.2991/icmmita-16.2016.237How to use a DOI?
Keywords
No-Reference; Image Mosaicing; Generalized Evidence Theory; Mean Structural Similarity
Abstract

No-reference image quality assessment is the future research direction in the field of image evaluation. A new no-reference image quality assessment based on the generalized evidence theory was proposed in this paper in order to deal with the measuring problem of the large scale samples under the optical microscope. The generalized basic probability assignment was generated by the triangular fuzzy numbers, based on the mean structural similarity. The decision was obtained by fusing the basic probability assignment with the generalized evidence theory.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
Series
Advances in Computer Science Research
Publication Date
January 2017
ISBN
978-94-6252-285-5
ISSN
2352-538X
DOI
10.2991/icmmita-16.2016.237How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yi She
AU  - Junjie Wu
AU  - Xin Chen
AU  - Guoqing Ding
AU  - Lihua Lei
AU  - Xiaoyu Cai
AU  - Jiasi Wei
PY  - 2017/01
DA  - 2017/01
TI  - No-Reference Image Mosaicing Method Based on the Generalized Evidence Theory
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-16.2016.237
DO  - 10.2991/icmmita-16.2016.237
ID  - She2017/01
ER  -