Super-Resolution Method Based on Edge Feature for High Resolution Imaging
Science Journal of Circuits, Systems and Signal Processing
Volume 3, Issue 6-1, December 2014, Pages: 24-29
Received: Nov. 29, 2014;
Accepted: Dec. 12, 2014;
Published: Dec. 27, 2014
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Ryohei Yamaguchi, Graduate School of Science and Technology, Seikei University, Tokyo, Japan
Teppei Sato, Graduate School of Science and Technology, Seikei University, Tokyo, Japan (Currently, ANA Holding Inc., Tokyo, Japan)
Atsushi Koike, Faculty of Science and Technology, Seikei University, Tokyo, Japan
Naoya Wada, Faculty of Science and Technology, Seikei University, Tokyo, Japan
Hitomi Murakami, Faculty of Science and Technology, Seikei University, Tokyo, Japan
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Super-resolution is recently one of the most attractive research themes. An image interpolation method using co-variance between neighboring pixels, so called New Edge-Directed Interpolation (NEDI), was proposed. It enables to interpolate pixels quantitatively regardless of edge features. However, in estimation of predictive coefficients and determination of NEDI’s local window size, edge features are not made consideration. So, NEDI cannot necessarily satisfy quality of picture. In order to overcome this problem, we propose a new intra-frame super-resolution method that window sizes and configurations are adaptively determined depending on edge strengths and orientations. Experimental simulation shows that the proposed method can interpolate pixels more clearly than NEDI for many kinds of edges.
Super-Resolution, Co-Variance, Bi-Linear Interpolation, Canny Edge Detection
To cite this article
Super-Resolution Method Based on Edge Feature for High Resolution Imaging, Science Journal of Circuits, Systems and Signal Processing. Special Issue: Computational Intelligence in Digital Image Processing.
Vol. 3, No. 6-1,
2014, pp. 24-29.
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