Yan Niu et al.
This project is a demo for our paper Low Cost Edge Sensing for High Quality Demosaicking.
All rights reserved.
This work is for acdamic purposes only. Commercial use is strictly prohibited without the author's permission.
This source code is written by Yan Niu ([email protected]).
This Matlab code implements the algorithm presented in our paper Low Cost Edge Sensing for High Quality Demosaicking, preprint, IEEE Transactions on Image Processing. If you use our code, please cite our paper.
The main file is run_LED( ).
An example use is to run" run_LED ('.\data\McM\')" in the command window of Matlab.
If you use the code in your work, please cite our paper:
@ARTICLE{8550686,
author={Y. {Niu} and J. {Ouyang} and W. {Zuo} and F. {Wang}},
journal={IEEE Transactions on Image Processing},
title={Low Cost Edge Sensing for High Quality Demosaicking},
year={2019},
volume={28},
number={5},
pages={2415-2427},
keywords={cameras;image colour analysis;image sampling;image segmentation;image sensors;optical filters;high quality demosaicking;color filter arrays;CFA;demosaicking procedure;RGB images;digital camera industry;demosaicking speed;demosaicking accuracy;HA pipeline;low cost edge sensing scheme;demosaicking algorithms;classical Hamilton-Adams algorithm;oversimplified interchannel smoothness formulation;oversimplified intrachannel smoothness formulation;Image color analysis;Interpolation;Image edge detection;Channel estimation;Correlation;Sensors;Logistics;Demosaicking;color filter array (CFA);Bayer pattern;logistic function},
doi={10.1109/TIP.2018.2883815},
ISSN={1057-7149},
month={May},}
Contact [email protected] for further questions regarding the code.
Nov. 25, 2018 by Yan Niu