An optimal factor analysis approach to improve the wavelet-based image resolution enhancement techniques

Date

2016-12-17

Free to read from

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Global Journal of Computer Science and Technology

Department

Type

Article

ISSN

0975-4350

Format

Citation

Wasnaa Witwit, Yitian Zhao, Karl Jenkins, Yifan Zhao. An optimal factor analysis approach to improve the wavelet-based image resolution enhancement techniques. Global Journal of Computer Science and Technology : F Graphics & Vision, Volume 16, Issue 3, 2016

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. The experimental results show that the proposed approach improves the performance of the selected image resolution enhancement methods and has potential to be extended to other methods.

Description

Software Description

Software Language

Github

Keywords

super-resolution, interpolation, discrete wavlet trasform (DWT)

DOI

Rights

Attribution 3.0 International

Relationships

Relationships

Supplements

Funder/s