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DOI: 10.14569/IJACSA.2020.0110833
PDF

Image Restoration based on Maximum Entropy Method with Parameter Estimation by Means of Annealing Method

Author 1: Kohei Arai

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 8, 2020.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Image restoration based on Maximum Entropy Method (MEM) with parameter estimation by means of annealing method is proposed. The proposed method allows spatial resolution enhancement. Using overlap sampling with a low resolution of sensor, high spatial resolution (corresponding to the sampling interval) can be achieved through ground data processing with image restoration methods. Through the experiments with simulation imagery data derived from Advanced Very High Resolution Radiometer (AVHRR) data, it was found that spatial resolution enhancement can be achieved, MEM is superior to the others when S/N ratio is poor (less than 33) while Conjugate Gradient Method (CGM) is superior when the S/N ratio is higher than 33. It was also found that the CGM is superior to the proposed method for the existing sampling jitter.

Keywords: Image restoration; Maximum Entropy Method (MEM); annealing; Advanced Very High Resolution Radiometer (AVHRR); Conjugate Gradient Method (CGM)

Kohei Arai, “Image Restoration based on Maximum Entropy Method with Parameter Estimation by Means of Annealing Method” International Journal of Advanced Computer Science and Applications(IJACSA), 11(8), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110833

@article{Arai2020,
title = {Image Restoration based on Maximum Entropy Method with Parameter Estimation by Means of Annealing Method},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110833},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110833},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {8},
author = {Kohei Arai}
}



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.

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