OW-SLR: Overlapping Windows on Semi-Local Region for Image Super-Resolution.

Autor:	Bhardwaj R; School of Optometry and Vision Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada., Jothi Balaji J; Department of Optometry, Medical Research Foundation, Chennai 600006, India., Lakshminarayanan V; School of Optometry and Vision Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
Jazyk:	angličtina
Zdroj:	Journal of imaging [J Imaging] 2023 Nov 08; Vol. 9 (11). Date of Electronic Publication: 2023 Nov 08.
DOI:	10.3390/jimaging9110246
Abstrakt:	There has been considerable progress in implicit neural representation to upscale an image to any arbitrary resolution. However, existing methods are based on defining a function to predict the Red, Green and Blue (RGB) value from just four specific loci. Relying on just four loci is insufficient as it leads to losing fine details from the neighboring region(s). We show that by taking into account the semi-local region leads to an improvement in performance. In this paper, we propose applying a new technique called Overlapping Windows on Semi-Local Region (OW-SLR) to an image to obtain any arbitrary resolution by taking the coordinates of the semi-local region around a point in the latent space. This extracted detail is used to predict the RGB value of a point. We illustrate the technique by applying the algorithm to the Optical Coherence Tomography-Angiography (OCT-A) images and show that it can upscale them to random resolution. This technique outperforms the existing state-of-the-art methods when applied to the OCT500 dataset. OW-SLR provides better results for classifying healthy and diseased retinal images such as diabetic retinopathy and normals from the given set of OCT-A images.
Databáze:	MEDLINE
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