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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.
Method for Image Source Separation by Means of Independent Component Analysis: ICA, Maximum Entory Method: MEM, and Wavelet Based Method: WBM
Digital Object Identifier (DOI) : 10.14569/IJACSA.2012.031113
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 3 Issue 11, 2012.
Abstract: Method for image source separation based on Independent Component Analysis: ICA, Maximum Entropy Method: MEM, and Wavelet Based Method: WBM is proposed. Experimental results show that image separation can be done from the combined different images by using the proposed method with an acceptable residual error.
Keywords: Blind separation; image separation; cucktail party effect; ICA; MEM; wavelet analuysis.
Kohei Arai, “Method for Image Source Separation by Means of Independent Component Analysis: ICA, Maximum Entory Method: MEM, and Wavelet Based Method: WBM” International Journal of Advanced Computer Science and Applications(IJACSA), 3(11), 2012. http://dx.doi.org/10.14569/IJACSA.2012.031113
@article{Arai2012,
title = {Method for Image Source Separation by Means of Independent Component Analysis: ICA, Maximum Entory Method: MEM, and Wavelet Based Method: WBM},
journal = {International Journal of Advanced Computer Science and Applications}
doi = {10.14569/IJACSA.2012.031113},
url = {http://dx.doi.org/10.14569/IJACSA.2012.031113},
year = {2012},
publisher = {The Science and Information Organization},
volume = {3},
number = {11},
author = {Kohei Arai},
}
