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Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Image noise Detection and Removal based on Enhanced GridLOF Algorithm
Digital Object Identifier (DOI) : 10.14569/IJACSA.2017.081260
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 12, 2017.
Abstract: Image noise removal is a major task in image processing where noise can harness any information inferred from the image especially when the noise level is high. Although there exists many outlier detection approaches used for this task, more enhancements are needed to achieve better performance specifically in terms of time. This paper proposes a new algorithm to detect and remove noise from images depending on an enhanced version of GridLOF algorithm. The enhancement aims to reduce the time and complexity of the algorithm while attaining comparable accuracy. Simulation results on a set of different images proved that proposed algorithm achieves the standard accuracy.
Keywords: Outlier detection; image noise removal; LOF; GridLOF
Ahmed M. Elmogy, Eslam Mahmoud and Fahd A. Turki, “Image noise Detection and Removal based on Enhanced GridLOF Algorithm” International Journal of Advanced Computer Science and Applications(IJACSA), 8(12), 2017. http://dx.doi.org/10.14569/IJACSA.2017.081260
@article{Elmogy2017,
title = {Image noise Detection and Removal based on Enhanced GridLOF Algorithm},
journal = {International Journal of Advanced Computer Science and Applications}
doi = {10.14569/IJACSA.2017.081260},
url = {http://dx.doi.org/10.14569/IJACSA.2017.081260},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {12},
author = {Ahmed M. Elmogy and Eslam Mahmoud and Fahd A. Turki},
}
