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    Denoising RENOIR Image Dataset with DBSR

    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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    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:
    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
    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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