Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-14581
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Main Title: Image interpolation using Shearlet based iterative refinement
Author(s): Lakshman, Haricharan
Lim, Wang-Q
Schwarz, Heiko
Marpe, Detlev
Kutyniok, Gitta
Wiegand, Thomas
Type: Research Paper
URI: https://depositonce.tu-berlin.de/handle/11303/15808
http://dx.doi.org/10.14279/depositonce-14581
License: http://rightsstatements.org/vocab/InC/1.0/
Abstract: This paper proposes an image interpolation algorithm exploiting sparse representation for natural images. It involves three main steps: (a) obtaining an initial estimate of the high resolution image using linear methods like FIR filtering, (b) promoting sparsity in a selected dictionary through iterative thresholding, and (c) extracting high frequency information from the approximation to refine the initial estimate. For the sparse modeling, a shearlet dictionary is chosen to yield a multiscale directional representation. The proposed algorithm is compared to several state-of-the-art methods to assess its objective as well as subjective performance. Compared to the cubic spline interpolation method, an average PSNR gain of around 0.8 dB is observed over a dataset of 200 images.
Subject(s): interpolation
sparse representation
shearlets
iterative refinement
algorithm
Issue Date: 10-Oct-2014
Date Available: 17-Dec-2021
Language Code: en
DDC Class: 510 Mathematik
MSC 2000: 65T60 Wavelets
41A05 Interpolation
Series: Preprint-Reihe des Instituts für Mathematik, Technische Universität Berlin
Series Number: 2014, 20
ISSN: 2197-8085
TU Affiliation(s): Fak. 2 Mathematik und Naturwissenschaften » Inst. Mathematik
Appears in Collections:Technische Universität Berlin » Publications

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