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dc.contributor.advisorBeltrán Castañón, César Armando
dc.contributor.authorPineda Ancco, Ferdinand Edgardo
dc.date.accessioned2020-03-18T00:42:20Z
dc.date.available2020-03-18T00:42:20Z
dc.date.created2020-03-18T00:42:20Z
dc.date.issued2020-03-17
dc.identifier.urihttp://hdl.handle.net/20.500.12404/16137
dc.description.abstractRecently, satellites in operation offering very high-resolution (VHR) images has experienced an important increase, but they remain as a smaller proportion against existing lower resolution (HR) satellites. Our work proposes an alternative to improve the spatial resolution of HR images obtained by Sentinel-2 satellite by using the VHR images from PeruSat1, a Peruvian satellite, which serve as the reference for the superresolution approach implementation based on a Generative Adversarial Network (GAN) model, as an alternative for obtaining VHR images. The VHR PeruSat-1 image dataset is used for the training process of the network. The results obtained were analyzed considering the Peak Signal to Noise Ratios (PSNR), the Structural Similarity (SSIM) and the Erreur Relative Globale Adimensionnelle de Synth`ese (ERGAS). Finally, some visual outcomes, over a given testing dataset, are presented so the performance of the model could be analyzed as well.
dc.language.isoeng
dc.publisherPontificia Universidad Católica del Perú
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.sourcePontificia Universidad Católica del Perú
dc.sourceRepositorio de Tesis - PUCP
dc.subjectSatélites artificiales en telecomunicaciones
dc.subjectProcesamiento de imágenes digitales
dc.titleA generative adversarial network approach for super resolution of sentinel-2 satellite images
dc.typeinfo:eu-repo/semantics/masterThesis
thesis.degree.nameMagíster en Informática con mención en Ciencias de la Computaciónes_ES
thesis.degree.levelMaestríaes_ES
thesis.degree.grantorPontificia Universidad Católica del Perú. Escuela de Posgradoes_ES
thesis.degree.disciplineInformática con mención en Ciencias de la Computaciónes_ES
dc.type.otherTesis de maestría
dc.publisher.countryPE
renati.discipline611087es_ES
renati.levelhttps://purl.org/pe-repo/renati/level#maestroes_ES
renati.typehttp://purl.org/pe-repo/renati/type#trabajoDeInvestigaciones_ES


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