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Zero-shot super-resolution with a physically-motivated downsampling kernel for endomicroscopy

Szczotka, AB; Shakir, DI; Clarkson, MJ; Pereira, SP; Vercauteren, T; (2021) Zero-shot super-resolution with a physically-motivated downsampling kernel for endomicroscopy. IEEE Transactions on Medical Imaging 10.1109/TMI.2021.3067512. (In press). Green open access

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Abstract

Super-resolution (SR) methods have seen significant advances thanks to the development of convolutional neural networks (CNNs). CNNs have been successfully employed to improve the quality of endomicroscopy imaging. Yet, the inherent limitation of research on SR in endomicroscopy remains the lack of ground truth high-resolution (HR) images, commonly used for both supervised training and reference-based image quality assessment (IQA). Therefore, alternative methods, such as unsupervised SR are being explored. To address the need for non-reference image quality improvement, we designed a novel zero-shot super-resolution (ZSSR) approach that relies only on the endomicroscopy data to be processed in a self-supervised manner without the need for ground-truth HR images. We tailored the proposed pipeline to the idiosyncrasies of endomicroscopy by introducing both: a physically-motivated Voronoi downscaling kernel accounting for the endomicroscope’s irregular fibre-based sampling pattern, and realistic noise patterns. We also took advantage of video sequences to exploit a sequence of images for self-supervised zero-shot image quality improvement. We run ablation studies to assess our contribution in regards to the downscaling kernel and noise simulation. We validate our methodology on both synthetic and original data. Synthetic experiments were assessed with reference-based IQA, while our results for original images were evaluated in a user study conducted with both expert and non-expert observers. The results demonstrated superior performance in image quality of ZSSR reconstructions in comparison to the baseline method. The ZSSR is also competitive when compared to supervised single-image SR, especially being the preferred reconstruction technique by experts.

Type: Article
Title: Zero-shot super-resolution with a physically-motivated downsampling kernel for endomicroscopy
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TMI.2021.3067512
Publisher version: https://dx.doi.org/10.1109/TMI.2021.3067512
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: blind super-resolution, endomicroscopy, video enhancement, zero-shot
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Inst for Liver and Digestive Hlth
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10124990
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