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Image zooming method using edge-directed moving least squares interpolation based on exponential polynomials

Title
Image zooming method using edge-directed moving least squares interpolation based on exponential polynomials
Authors
Lee, Yeon JuYoon, Jungho
Ewha Authors
윤정호
SCOPUS Author ID
윤정호scopus
Issue Date
2015
Journal Title
APPLIED MATHEMATICS AND COMPUTATION
ISSN
0096-3003JCR Link1873-5649JCR Link
Citation
vol. 269, pp. 569 - 583
Keywords
Moving least squaresExponential polynomialReproducing propertyEdge-directed interpolationImage upsamplingMinimization problem
Publisher
ELSEVIER SCIENCE INC
Indexed
SCIE; SCOPUS WOS scopus
Abstract
This paper presents a nonlinear image interpolation algorithm. The suggested method is based on the moving least squares (MLS) projection technique, but introduces a fundamental modification. The algebraic polynomial-based MLS methods provide very satisfactory results. However, the associated approximation space is shift-and-scale invariant so that it cannot be adjusted according to the characteristic of a given data. As a result, when upsampling images, it has a limitation in producing sharp edges such that edges are often blurred in the magnified images. To recover sharper edges, we need to reduce smoothing parameter or adapt a new parameter sharpening the edges. Motivated by this observations, we propose a novel MLS method governed by a set of exponential polynomials with tension parameters such that they can be tuned to the characteristic of given data. Moreover, for a better match to the local structures around the edges, the suggested algorithm uses weights which consider the edge orientation. Numerical results are presented and compared, visually and by using some quantitative fidelity measures (PSNR, EPSNR, SSIM and FSIM), to the bicubic spline interpolation and other recently developed nonlinear methods. The results demonstrate the new algorithm's ability to magnify an image while preserving edge features. (C) 2015 Elsevier Inc. All rights reserved.
DOI
10.1016/j.amc.2015.07.086
Appears in Collections:
자연과학대학 > 수학전공 > Journal papers
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