wangke0809 / LQSR

Learning-based joint super-resolution and deblocking for a highly compressed image

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Program: Single Image Super-Resolution of a Highly Compressed Image Authors: Chih-Chung Hsu (m121754@gmail.com) Citation format: L.W. Kang, C.C. Hsu, B.Q. Zhuang, C.W. Lin, and C.H. Yeh, “Learning-based joint super-resolution and deblocking for a highly compressed image,” IEEE Transactions on Multimedia, vol. 17, no. 7, pp. 921−934, July 2015.

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Note that our parameters may different from paper described. However, our performance of this released code is similar to that of paper.

The main file is "Demo_Proposed.m". In commend line in Matlab, you can type Demo_Proposed to get the final super-resolved results. Note that this code only can run in Matlab 32bit version.

If there is any problem, please contact with me.

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Programming language: Matlab 2014b 32bit OS: Windows 10 preview x64 Database: Collected from ScSR code.

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Learning-based joint super-resolution and deblocking for a highly compressed image


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Language:MATLAB 100.0%