High-Resolution Reconstructions of Aerial Images Based on Deep Learning



Document title: High-Resolution Reconstructions of Aerial Images Based on Deep Learning
Journal: Computación y sistemas
Database:
System number: 000560630
ISSN: 1405-5546
Authors: 1
1
2
2
Institutions: 1Universidad Tecnológica de la Mixteca, Graduate Studies Division, Oaxaca. México
2Tokyo University of Science, Faculty of Science and Technology, Japón
Year:
Season: Oct-Dic
Volumen: 25
Number: 4
Pages: 739-749
Country: México
Language: Inglés
English abstract We present a methodology for high-resolution orthomosaic reconstruction using aerial images. Our proposal consists a neural network with two main stages, one to obtain the correspondences necessary to perform a LR-orthomosaic and another one that uses these results to generate an HR- orthomosaic, and a feedback connection. The CNN are based on well known models and are trained to perform image stitching and obtain a high-resolution orthomosaic. The results obtained in this work show that our methodology provides similar results to those obtained by an expert in orthophotography, but in high-resolution.
Keyword: Deep learning,
CNN,
2D reconstruction,
Aerial images,
Orthophotography,
Photogrammetry
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