Denoising RENOIR Image Dataset with DBSR

Authors

Fatma Albluwi, Trinity College Dublin, Ireland
Vladimir A. Krylov, Trinity College Dublin
Rozenn Dahyot, Trinity College Dublin

Document Type

Article

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

2. ENGINEERING AND TECHNOLOGY

Publication Details

IMVIP 2019: Irish Machine Vision & Image Processing, Technological University Dublin, Dublin, Ireland, August 28-30.

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.

DOI

http://doi.org10.21427/g34k-8r27

Recommended Citation

Albluwi, F., Krylov, V. & Dahyot, R. (2019). Denoising RENOIR dataset with DBSR, IMVIP 2019: Irish Machine Vision & Image Processing, Technological University Dublin, Dublin, Ireland, August 28-30. doi: 10.21427/g34k-8r27