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

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...

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Autores principales: Bhardwaj, Rishav, Jothi Balaji, Janarthanam, Lakshminarayanan, Vasudevan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10672420/
https://www.ncbi.nlm.nih.gov/pubmed/37998093
http://dx.doi.org/10.3390/jimaging9110246
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author Bhardwaj, Rishav
Jothi Balaji, Janarthanam
Lakshminarayanan, Vasudevan
author_facet Bhardwaj, Rishav
Jothi Balaji, Janarthanam
Lakshminarayanan, Vasudevan
author_sort Bhardwaj, Rishav
collection PubMed
description 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.
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spelling pubmed-106724202023-11-08 OW-SLR: Overlapping Windows on Semi-Local Region for Image Super-Resolution Bhardwaj, Rishav Jothi Balaji, Janarthanam Lakshminarayanan, Vasudevan J Imaging Article 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. MDPI 2023-11-08 /pmc/articles/PMC10672420/ /pubmed/37998093 http://dx.doi.org/10.3390/jimaging9110246 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bhardwaj, Rishav
Jothi Balaji, Janarthanam
Lakshminarayanan, Vasudevan
OW-SLR: Overlapping Windows on Semi-Local Region for Image Super-Resolution
title OW-SLR: Overlapping Windows on Semi-Local Region for Image Super-Resolution
title_full OW-SLR: Overlapping Windows on Semi-Local Region for Image Super-Resolution
title_fullStr OW-SLR: Overlapping Windows on Semi-Local Region for Image Super-Resolution
title_full_unstemmed OW-SLR: Overlapping Windows on Semi-Local Region for Image Super-Resolution
title_short OW-SLR: Overlapping Windows on Semi-Local Region for Image Super-Resolution
title_sort ow-slr: overlapping windows on semi-local region for image super-resolution
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10672420/
https://www.ncbi.nlm.nih.gov/pubmed/37998093
http://dx.doi.org/10.3390/jimaging9110246
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