Abstract
The application of soft computing in image/signal enhancement and comparing it with traditional methods will be discussed in this paper. This study presents two optimization methods for α-rooting image enhancement, which is a transform based method. The first method is a derivative-based optimization and the second one is Genetic Algorithm optimization. The parameter will be driven through optimization of measure of enhancement function (EME). The results from, the simulations show both methods are reliable; however, the first method has more computing cost.
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© 2014 Springer International Publishing Switzerland
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Ezell, M., Motaghi, A., Jamshidi, M. (2014). Alpha-Rooting Image Enhancement Using a Traditional Algorithm and Genetic Algorithm. In: Jamshidi, M., Kreinovich, V., Kacprzyk, J. (eds) Advance Trends in Soft Computing. Studies in Fuzziness and Soft Computing, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-319-03674-8_29
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DOI: https://doi.org/10.1007/978-3-319-03674-8_29
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03673-1
Online ISBN: 978-3-319-03674-8
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