Albluwi, Fatma and Vladimir, A. Krylov and Dahyot, Rozenn (2019) Denoising RENOIR Image Dataset with DBSR. IMVIP 2019: Irish Machine Vision and Image Processing.

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Abstract

Noise reduction algorithms have often been evaluated using images degraded by artificially synthesised noise. The RENOIR image dataset [3] 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) [2] to reduce the natural noise due to low light conditions in a RENOIR dataset.

Item Type:	Article
Keywords:	image denoising; super-reolution; RENOIR dataset; DBSR;
Academic Unit:	Faculty of Science and Engineering > Computer Science
Item ID:	15156
Identification Number:	https://doi.org/10.21427/g34k-8r27
Depositing User:	Rozenn Dahyot
Date Deposited:	20 Dec 2021 12:45
Journal or Publication Title:	IMVIP 2019: Irish Machine Vision and Image Processing
Publisher:	Arrow @ TU Dublin
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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