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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.
Category Decomposition Method for Un-Mixing of Mixels Acquired with Spaceborne Based Visible and Near Infrared Radiometers by Means of Maximum Entropy Method with Parameter Estimation Based on Simulated Annealing
Digital Object Identifier (DOI) : 10.14569/IJARAI.2013.020410
Article Published in International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 2 Issue 4, 2013.
Abstract: Category decomposition method for un-mixing of mixels (Mixed Pixels) which is acquired with spaceborne based visible to near infrared radiometers by means of Maximum Entropy Method (MEM) with parameter estimation based on Simulated Annealing: SA is proposed. Through simulation studies with spectral characteristics of the ground cover targets which are derived from spectral library and actual remote sensing satellite imagery data, it is confirmed that the proposed method works well.
Keywords: category decomposition; mixed pixel; satellite remote sensing; maximum entropy method; simulated annealing; spectral library
Kohei Arai, “Category Decomposition Method for Un-Mixing of Mixels Acquired with Spaceborne Based Visible and Near Infrared Radiometers by Means of Maximum Entropy Method with Parameter Estimation Based on Simulated Annealing ” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 2(4), 2013. http://dx.doi.org/10.14569/IJARAI.2013.020410
@article{Arai2013,
title = {Category Decomposition Method for Un-Mixing of Mixels Acquired with Spaceborne Based Visible and Near Infrared Radiometers by Means of Maximum Entropy Method with Parameter Estimation Based on Simulated Annealing },
journal = {International Journal of Advanced Research in Artificial Intelligence}
doi = {10.14569/IJARAI.2013.020410},
url = {http://dx.doi.org/10.14569/IJARAI.2013.020410},
year = {2013},
publisher = {The Science and Information Organization},
volume = {2},
number = {4},
author = {Kohei Arai},
}
