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CRC-SISR

Matlab code for Collaborative Representation Cascade for Single-Image Super-Resolution

% Collaborative Representation Cascade for Single-Image Super-Resolution % Example code

% This code is built on the example code of "Anchored Neighborhood % Regression for Fast Example-Based Super-Resolution".

% Please refere to papers: % [1] Radu Timofte, Vincent De Smet, Luc Van Gool. % Anchored Neighborhood Regression for Fast Example-Based Super-Resolution. % International Conference on Computer Vision (ICCV), 2013.

% [2] Radu Timofte, Vincent De Smet, Luc Van Gool. % A+: Adjusted Anchored Neighborhood Regression for Fast Super-Resolution. % Asian Conference on Computer Vision (ACCV), 2014.

% [3] Yongbing Zhang, Yulun Zhang, Jian Zhang, Dong Xu, Yun Fu, Yisen Wang, Xiangyang Ji, Qionghai Dai % Collaborative Representation Cascade for Single-Image Super-Resolution % IEEE Transactions on Systems, Man, and Cybernetics: Systems (TSMC), vol. PP, no. 99, pp. 1-16, 2017.

% [4] Yulun Zhang, Kaiyu Gu, Yongbing Zhang, Jian Zhang, Qionghai Dai % Image Super-Resolution based on Dictionary Learning and Anchored Neighborhood Regression with Mutual Inconherence % IEEE International Conference on Image Processing (ICIP2015), Quebec, Canada, Sep. 2015.

% [5] Yulun Zhang, Yongbing Zhang, Jian Zhang, Haoqian Wang, Qionghai Dai % Single Image Super-Resolution via Iterative Collaborative Representation % Paci?c-Rim Conference on Multimedia (PCM2015), Gwangju, Korea, Sep. 2015.

% For any questions, email me by yulun100@gmail.com

% Usage Run 'Demo_CRC.m'.

upscaling = 2; % the magnification factor x2, x3, x4...

input_dir = 'Set10Dong'; % Set5, Set14, Set10Dong, SetSRF

pattern = '*.bmp'; % Pattern to process

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