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

An Infrared Image Super-resolution Reconstruction Method Based on Compressive Sensing

Authors
Yuxing Mao, Yan Wang, Jintao Zhou, Haiwei Jia
Corresponding Author
Yuxing Mao
Available Online March 2016.
DOI
10.2991/icmmct-16.2016.244How to use a DOI?
Keywords
Infrared image, SRR, CS, difference operation, OMP
Abstract

Limited by the properties of infrared detector and camera lens, infrared images are often detail missing and indistinct in vision. The spatial resolution needs to be improved to satisfy the requirements of practical application. Based on compressive sensing (CS) theory, this thesis presents a single image super-resolution reconstruction (SRR) method. With synthetically adopting image degradation model, difference operation-based sparse transformation method and orthogonal matching pursuit (OMP) algorithm, the image SRR problem is transformed into a sparse signal reconstruction issue in CS theory. In our work, the sparse transformation matrix is obtained through difference operation to image, and, the measurement matrix is achieved analytically from the imaging principle of infrared camera. Therefore, the time consumption can be decreased compared with the redundant dictionary obtained by sample training such as K-SVD. The experimental results show that our method can achieve favorable performance and good stability with low algorithm complexity.

Copyright
© 2016, 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/).

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Volume Title
Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
Series
Advances in Engineering Research
Publication Date
March 2016
ISBN
10.2991/icmmct-16.2016.244
ISSN
2352-5401
DOI
10.2991/icmmct-16.2016.244How to use a DOI?
Copyright
© 2016, 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  - Yuxing Mao
AU  - Yan Wang
AU  - Jintao Zhou
AU  - Haiwei Jia
PY  - 2016/03
DA  - 2016/03
TI  - An Infrared Image Super-resolution Reconstruction Method Based on Compressive Sensing
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
PB  - Atlantis Press
SP  - 1242
EP  - 1249
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-16.2016.244
DO  - 10.2991/icmmct-16.2016.244
ID  - Mao2016/03
ER  -