Denoising RENOIR Image Dataset with DBSR. Fatma Albluwi, V. A. K. and Dahyot, R. In Irish Machine Vision and Image Processing (IMVIP 2019), volume ISBN 978-0-9934207-4-0, pages 76-79, Technological University Dublin, 28-30 August, 2019.
Denoising RENOIR Image Dataset with DBSR [link]Paper  doi  abstract   bibtex   1 download  
Noise reduction algorithms have often been evaluated using images degraded by artificially synthesised noise. The RENOIR image dataset provides an alternative way for testing noise reduction algorithms on real noisy images and we propose in this paper to assess our CNN called De-Blurring Super-Resolution (DBSR) to reduce the natural noise due to low light conditions in a RENOIR dataset.
@inproceedings{IMVIP2019Albluwi, 
title= {Denoising RENOIR Image Dataset with DBSR}, 
author= {Fatma Albluwi, Vladimir A. Krylov and R. Dahyot},
abstract={Noise reduction algorithms have often been evaluated using images degraded by artificially synthesised
noise. The RENOIR image dataset  provides an alternative way for testing noise reduction algorithms
on real noisy images and we propose in this paper to assess our CNN called De-Blurring Super-Resolution
(DBSR)  to reduce the natural noise due to low light conditions in a RENOIR dataset.},
booktitle= {Irish Machine Vision and Image Processing (IMVIP 2019)}, 
address= {Technological University Dublin}, month= {28-30 August}, 
year= {2019}, 
url={https://arrow.tudublin.ie/cgi/viewcontent.cgi?article=1006&context=impstwo},
doi={10.21427/g34k-8r27},
pages= {76-79}, 
volume= {ISBN 978-0-9934207-4-0}}
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