Fast Directional Dictionary Interpolation Super Resolution Algorithm in Medium and Low Magnification

In a real-time medium and low magnification super resolution display system, a fast medium and low magnification super resolution algorithm using all directional dictionary and fitting interpolation is proposed to improve the reconstruction image performance and reduce the computational complexity....

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Main Author: WANG Zhongfei, WANG Biao
Format: Article
Language:zho
Published: Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press 2020-02-01
Series:Jisuanji kexue yu tansuo
Subjects:
Online Access:http://fcst.ceaj.org/CN/abstract/abstract2123.shtml
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spelling doaj-d8f6bc1755604180842f22bda36aae0c2021-08-09T10:25:39ZzhoJournal of Computer Engineering and Applications Beijing Co., Ltd., Science PressJisuanji kexue yu tansuo1673-94182020-02-0114233634310.3778/j.issn.1673-9418.1901061Fast Directional Dictionary Interpolation Super Resolution Algorithm in Medium and Low MagnificationWANG Zhongfei, WANG Biao0School of Mathematics and Information Science, Baoji University of Arts and Sciences, Baoji, Shaanxi 721013, ChinaIn a real-time medium and low magnification super resolution display system, a fast medium and low magnification super resolution algorithm using all directional dictionary and fitting interpolation is proposed to improve the reconstruction image performance and reduce the computational complexity. For every interpolated pixel in high resolution image, first of all, the main texture direction of the corresponding interpolation interval in low resolution image is obtained through the pyramid texture dictionary. Then, the interpolation direction is modified based on the interpolated pixel position. Finally, the interpolation result is obtained by the unidirectional fitting interpolation. Simulation results show that compared with SREO (super resolution using edge orientation based on linear mapping), the proposed algorithm improves PSNR (peak signal to noise ratio) and SSIM (structural similarity) by 0.73 dB and 0.04 averagely and respectively. Moreover, the average computation time is reduced about 40% in the proposed algorithm.http://fcst.ceaj.org/CN/abstract/abstract2123.shtmlsuper resolutionmedium and low magnificationtexture; interpolation
collection DOAJ
language zho
format Article
sources DOAJ
author WANG Zhongfei, WANG Biao
spellingShingle WANG Zhongfei, WANG Biao
Fast Directional Dictionary Interpolation Super Resolution Algorithm in Medium and Low Magnification
Jisuanji kexue yu tansuo
super resolution
medium and low magnification
texture; interpolation
author_facet WANG Zhongfei, WANG Biao
author_sort WANG Zhongfei, WANG Biao
title Fast Directional Dictionary Interpolation Super Resolution Algorithm in Medium and Low Magnification
title_short Fast Directional Dictionary Interpolation Super Resolution Algorithm in Medium and Low Magnification
title_full Fast Directional Dictionary Interpolation Super Resolution Algorithm in Medium and Low Magnification
title_fullStr Fast Directional Dictionary Interpolation Super Resolution Algorithm in Medium and Low Magnification
title_full_unstemmed Fast Directional Dictionary Interpolation Super Resolution Algorithm in Medium and Low Magnification
title_sort fast directional dictionary interpolation super resolution algorithm in medium and low magnification
publisher Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
series Jisuanji kexue yu tansuo
issn 1673-9418
publishDate 2020-02-01
description In a real-time medium and low magnification super resolution display system, a fast medium and low magnification super resolution algorithm using all directional dictionary and fitting interpolation is proposed to improve the reconstruction image performance and reduce the computational complexity. For every interpolated pixel in high resolution image, first of all, the main texture direction of the corresponding interpolation interval in low resolution image is obtained through the pyramid texture dictionary. Then, the interpolation direction is modified based on the interpolated pixel position. Finally, the interpolation result is obtained by the unidirectional fitting interpolation. Simulation results show that compared with SREO (super resolution using edge orientation based on linear mapping), the proposed algorithm improves PSNR (peak signal to noise ratio) and SSIM (structural similarity) by 0.73 dB and 0.04 averagely and respectively. Moreover, the average computation time is reduced about 40% in the proposed algorithm.
topic super resolution
medium and low magnification
texture; interpolation
url http://fcst.ceaj.org/CN/abstract/abstract2123.shtml
work_keys_str_mv AT wangzhongfeiwangbiao fastdirectionaldictionaryinterpolationsuperresolutionalgorithminmediumandlowmagnification
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