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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Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
2020-02-01
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Online Access: | http://fcst.ceaj.org/CN/abstract/abstract2123.shtml |
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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 |
_version_ |
1721214189021691904 |