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Math. Comput. Appl. 2016, 21(4), 48; doi:10.3390/mca21040048

Rational Spline Image Upscaling with Constraint Parameters

1
School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan 250014, China
2
School of Mathematics, Shandong University, Jinan 250100, China
3
School of Computer Science and Technology, Shandong University, Jinan 250101, China
*
Author to whom correspondence should be addressed.
Academic Editor: Junjie Cao
Received: 30 September 2016 / Revised: 14 November 2016 / Accepted: 14 November 2016 / Published: 13 December 2016
(This article belongs to the Special Issue Information and Computational Science)
View Full-Text   |   Download PDF [1416 KB, uploaded 13 December 2016]   |  

Abstract

Image interpolation is one of key contents in image processing. We present an interpolation algorithm based on a rational function model with constraint parameters. Firstly, based on the construction principle of the rational function, the detection threshold is selected through contour analysis. The smooth and non-smooth areas are interpolated by bicubic interpolation and general rational interpolation, respectively. In order to enhance the contrast in non-smooth areas and preserve the details, the parameter optimization technique is applied to get optimal shape parameters. Experimental results on benchmark test images demonstrate that the proposed method achieves competitive performance with the state-of-the-art interpolation algorithms, especially in image details and texture features. View Full-Text
Keywords: rational function; adaptive interpolation; region division; parameters optimization rational function; adaptive interpolation; region division; parameters optimization
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Yao, X.; Zhang, Y.; Bao, F.; Zhang, C. Rational Spline Image Upscaling with Constraint Parameters. Math. Comput. Appl. 2016, 21, 48.

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