Rational Spline Image Upscaling with Constraint Parameters
AbstractImage 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
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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.
Yao X, Zhang Y, Bao F, Zhang C. Rational Spline Image Upscaling with Constraint Parameters. Mathematical and Computational Applications. 2016; 21(4):48.Chicago/Turabian Style
Yao, Xunxiang; Zhang, Yunfeng; Bao, Fangxun; Zhang, Caiming. 2016. "Rational Spline Image Upscaling with Constraint Parameters." Math. Comput. Appl. 21, no. 4: 48.
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