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Pan-sharpening of WorldView-2 images with deep learning

Authors: Jové Caballero, Miquel;

Pan-sharpening of WorldView-2 images with deep learning

Abstract

En los últimos años el incremento exponencial del interés por el Aprendizaje Profundo ha tenido un gran impacto en la mejora de la resolución de imágenes. En particular, enriquecer la calidad de las imágenes captadas con teledetección es un campo donde distintos investigadores han propuesto varios modelos. Uno de estos enfoques es el pan-sharpening, que aprovecha los pares de imágenes de los satélites para incrementar la resolución de imágenes multiespectrales o hiperespectrales. En este proyecto, un modelo de la literatura se adaptará para imágenes del satélite WorldView-2 y será modificado para mejorar los resultados establecidos en la actualidad por el modelo. Los resultados de los experimentos se compararán entre el modelo adaptado y el modelo modificado para verificar que los cambios realizados son efectivos.

En els darrers anys l'increment exponencial de l'interès per l'Aprenentatge Profund ha tingut un gran impacte en la millora de la resolució d'imatges. En particular, enriquir la qualitat de les imatges captades per teledetecció és un camp diferents investigadors han proposat diversos models. Un d'aquests enfocaments és el pan-sharpening, que aprofita els parells d'imatges dels satél·lits per incrementar la resolució d'imatges multiespectrals o hiperespectrals. En aquest projecte, un model de la literatura s'adaptará per a imatges del satél·lit WorldView-2 i será modificat per millorar els resultats establerts pel model actualment. Els resultats dels experiments es compararan entre el model adaptat i el model modificat per tal de verificar l'efectivitat del canvis realitzats.

In recent years the exponential growth on Deep Learning interest has had a huge impact on improving the resolution of images. In particular, enhancing the quality of remote sensing imagery is a field where many models have been proposed by different researchers. One of this approaches is pan-sharpening, which takes advantage from the satellites imagery pairs in order to raise the resolution of multispectral or hyperspectral images. In this project, a model from the literature will be adapted for WorldView-2 satellite imagery and modified to improve the current stated results from the model. Experiments results will be compared between the adapted model and the modified one so the adjustments effectiveness can be proven.

Country
Spain
Keywords

Artificial intelligence, :Informàtica::Intel·ligència artificial::Aprenentatge automàtic [Àrees temàtiques de la UPC], Intel·ligència artificial, Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic, Image generation, Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo, Imatges -- Processament, :Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo [Àrees temàtiques de la UPC], Procesado de imágenes, Aprendizaje automático, Inteligencia artificial, Deep Learning, Image processing, Machine learning, Generación de imágenes, Aprenentatge automàtic

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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