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The existing wavelet-based image resolution enhancement techniques have many assumptions, such as limitation of the way to generate low-resolution images and the selection of wavelet functions, which limits their applications in different fields. This paper initially identifies the factors that effectively affect the performance of these techniques and quantitatively evaluates the impact of the existing assumptions. An approach called Optimal Factor Analysis employing the genetic algorithm is then introduced to increase the applicability and fidelity of the existing methods. Moreover, a new Figure of Merit is proposed to assist the selection of parameters and better measure the overall performance.
Yitian Zhao. 2016. "An Optimal Factor Analysis Approach to Improve the Wavelet-based Image Resolution Enhancement Techniques". Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 16 (GJCST Volume 16 Issue F3).
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
v1.2
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Total Score: 174
Country: United Kingdom
Subject: Global Journal of Computer Science and Technology
Authors: Wasnaa Witwit, Yitian Zhao, Karl Jenkins, Yifan Zhao (PhD/Dr. count: 0)
View Count (all-time): 443
Total Views (Real + Logic): 3078
Total Downloads (simulated): 134
Publish Date: 2016 01, Fri
Monthly Totals (Real + Logic):
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