An Optimal Factor Analysis Approach to Improve the Wavelet-based Image Resolution Enhancement Techniques

An Optimal Factor Analysis Approach to Improve the Wavelet-based Image Resolution Enhancement Techniques

Yitian Zhao

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Wasnaa Witwit

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Karl Jenkins

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Yifan Zhao

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Cranfield University

An Optimal Factor Analysis Approach to Improve the Wavelet-based Image Resolution Enhancement Techniques

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Abstract

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.

References

26 Cites in Article

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Yitian Zhao. 2016. \u201cAn Optimal Factor Analysis Approach to Improve the Wavelet-based Image Resolution Enhancement Techniques\u201d. Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 16 (GJCST Volume 16 Issue F3).

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GJCST Volume 16 Issue F3

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Classification

GJCST-F Classification I.3.3

I.4

B.4.2

H.2.8

Submission ReceivedDecember 10, 2015
Peer Review Double Blind
Handling Editor
Accepted January 3, 2016
Published January 15, 2016

Version of record

v1.2

Issue date

December 17, 2016

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Article Matrices

Total Score: 134

Country: United Kingdom

Subject: Global Journal of Computer Science and Technology - F: Graphics & Vision

Authors: Wasnaa Witwit, Yitian Zhao, Karl Jenkins, Yifan Zhao (PhD/Dr. count: 0)

View Count (all-time): 277

Total Views (Real + Logic): 7070

Total Downloads (simulated): 2003

Publish Date: 2016 12, Sat

Monthly Totals (Real + Logic):

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Total Views: 7070

Total Downloads: 2003

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