Resumen

RODRIGUEZ-SANTIAGO, Armando Levid; ARIAS-AGUILAR, José Aníbal; TAKEMURA, Hiroshi  y  PETRILLI-BARCELO, Alberto Elías. High-Resolution Reconstructions of Aerial Images Based on Deep Learning. Comp. y Sist. [online]. 2021, vol.25, n.4, pp.739-749.  Epub 28-Feb-2022. ISSN 2007-9737.  https://doi.org/10.13053/cys-25-4-4047.

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.

Palabras llave : Deep learning; CNN; 2D reconstruction; aerial images; orthophotography; photogrammetry.

        · texto en Inglés     · Inglés ( pdf )