A New Algorithm for Image Resizing Based on Bivariate Rational Interpolation

Authors:
Shanshan Gao;Caiming Zhang;Yunfeng Zhang
Affiliations:
School of Computer Science and Technology, Shandong University, China and School of Computer Science and Technology, Shandong Economic University, China;School of Computer Science and Technology, Shandong University, China and School of Computer Science and Technology, Shandong Economic University, China;School of Computer Science and Technology, Shandong Economic University, China
Venue:
ICCS 2009 Proceedings of the 9th International Conference on Computational Science
Year:
2009

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Abstract

A new method for image resizing by bivariate rational interpolation based on function values and partial derivative value is presented. When an original image is resized in an arbitrary ratio, the first step of the method is constructing the rational interpolation fitting the original surface where the given image data points are sampled from. The resized image can be obtained just by re-sampling on the interpolation surface. The algorithm presents how to estimate the partial derivative value of image data point needed for rational interpolation, and at same time considers the adjustment of tangent vector of the edge point to keep edges well defined. Various experiments are presented to show efficiency of the proposed method and that the resized images can preserve clear and sharp borders and hence offer more detail information in real application.