Deep-Learning Based Super-Resolution of Aeolianite Images on the Purpose of Edge Detection and Pattern Extraction

Antigoni Panagiotopoulou, Lemonia Ragia, Niki Evelpidou

2023

Abstract

In the current work processing of Aeolianite images, from a quarry in the island of Naxos in Greece, is presented. The deep-learning based technique called Densely Residual Laplacian Super-Resolution (DRLN) is applied on the original images of size 3000×4000 pixels to increase their spatial resolution per the factor of 4. Edge detection is applied on the initial images as well as on the super-resolved images of 12000×16000 pixels. Visual and numerical comparisons on several Aeolianite scenes prove that the super-resolved images are advantageous in relation to the initial images of lower spatial resolution, as far as edge detection and pattern delineation are concerned. The improvement in edge detected components reaches 83%. Classification or pattern extraction could significantly benefit from encompassing the proposed methodology for Aeolianite images as a preprocessing step.

Paper Citation

in Harvard Style

Panagiotopoulou A., Ragia L. and Evelpidou N. (2023). Deep-Learning Based Super-Resolution of Aeolianite Images on the Purpose of Edge Detection and Pattern Extraction. In Proceedings of the 9th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM, ISBN 978-989-758-649-1, SciTePress, pages 244-250. DOI: 10.5220/0012038600003473

in Bibtex Style

@conference{gistam23,
author={Antigoni Panagiotopoulou and Lemonia Ragia and Niki Evelpidou},
title={Deep-Learning Based Super-Resolution of Aeolianite Images on the Purpose of Edge Detection and Pattern Extraction},
booktitle={Proceedings of the 9th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,},
year={2023},
pages={244-250},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012038600003473},
isbn={978-989-758-649-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,
TI - Deep-Learning Based Super-Resolution of Aeolianite Images on the Purpose of Edge Detection and Pattern Extraction
SN - 978-989-758-649-1
AU - Panagiotopoulou A.
AU - Ragia L.
AU - Evelpidou N.
PY - 2023
SP - 244
EP - 250
DO - 10.5220/0012038600003473
PB - SciTePress