Super-resolution based on Edge-aware Sparse Representation Via Multiple Dictionaries

Muhammad Haris, Hajime Nobuhara

2016

Abstract

In this paper, we propose a new edge-aware super-resolution algorithm based on sparse representation via multiple dictionaries. The algorithm creates multiple pairs of dictionaries based on selective sparse representation. The dictionaries are clustered based on the edge orientation that categorized into 5 clusters: 0, 45, 90, 135, and non-direction. The proposed method is conceivably able to reduce blurring, blocking, and ringing artifacts in edge areas, compared with other methods. The experiment uses 900 natural grayscale images taken from USC SIPI Database. It is confirmed that our proposed method is better than current state-of-the-art algorithms. To amplify the evaluation, we use four evaluation indexes: higher peak signal-to-noise ratio (PSNR), structural similarity (SSIM), feature similarity (FSIM) index, and time. On 3x magnification experiment, our proposed method has the highest value for all evaluation compare to other methods by 11%, 14%, 6% in terms of PSNR, SSIM, and FSIM respectively. It is also proven that our proposed method has shorter execution time compare to other methods.

Paper Citation

in Harvard Style

Haris M. and Nobuhara H. (2016). Super-resolution based on Edge-aware Sparse Representation Via Multiple Dictionaries.In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 40-47. DOI: 10.5220/0005723300400047

in Bibtex Style

@conference{visapp16,
author={Muhammad Haris and Hajime Nobuhara},
title={Super-resolution based on Edge-aware Sparse Representation Via Multiple Dictionaries},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={40-47},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005723300400047},
isbn={978-989-758-175-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)
TI - Super-resolution based on Edge-aware Sparse Representation Via Multiple Dictionaries
SN - 978-989-758-175-5
AU - Haris M.
AU - Nobuhara H.
PY - 2016
SP - 40
EP - 47
DO - 10.5220/0005723300400047