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Research Article | Open Access |

An Example-based Super-Resolution Algorithm for Multi-Spectral Remote Sensing Images

Author 1: W. Jino Hans Author 2: Lysiya Merlin.S Author 3: Venkateswaran N Author 4: Divya Priya T
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 7, No. 9 · Published 2016

DOI: https://doi.org/10.14569/IJACSA.2016.070945

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Abstract

This paper proposes an example-based super-resolution algorithm for multi-spectral remote sensing images. The underlying idea of this algorithm is to learn a matrix-based implicit prior from a set of high-resolution training examples to model the relation between LR and HR images. The matrix-based implicit prior is learned as a regression operator using conjugate decent method. The direct relation between LR and HR image is obtained from the regression operator and it is used to super-resolve low-resolution multi-spectral remote sensing images. A detailed performance evaluation is carried out to validate the strength of the proposed algorithm.

Keywords

Remote sensing Super-resolution Image-pair analysis Regression operators

How to Cite this Article

Hans, W. J., Merlin.S, L., N, V., & T, D. P. (2016). An Example-based Super-Resolution Algorithm for Multi-Spectral Remote Sensing Images. International Journal of Advanced Computer Science and Applications, 7(9). https://doi.org/10.14569/IJACSA.2016.070945

Hans, W. Jino, et al.. "An Example-based Super-Resolution Algorithm for Multi-Spectral Remote Sensing Images." International Journal of Advanced Computer Science and Applications, vol. 7, no. 9, 2016, https://doi.org/10.14569/IJACSA.2016.070945.

@article{Hans2016,
  title     = {An Example-based Super-Resolution Algorithm for Multi-Spectral Remote Sensing Images},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {9},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {W. Jino Hans and Lysiya Merlin.S and Venkateswaran N and Divya Priya T},
  doi       = {10.14569/IJACSA.2016.070945},
  url       = {https://doi.org/10.14569/IJACSA.2016.070945}
}

Open Access — licensed under a Creative Commons Attribution 4.0 International License. Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.

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