Super Resolution Approach Using Generative Adversarial Network Models for Improving Satellite Image Resolution

Ferdinand Pineda, Victor Ayma, Robert Aduviri, Cesar Beltran

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

Recently, the number of satellite imaging sensors deployed in space has experienced a considerable increase, but most of these sensors provide low spatial resolution images, and only a small proportion contribute with images at higher resolutions. This work proposes an alternative to improve the spatial resolution of Landsat-8 images to the reference of Sentinel-2 images, by applying a Super Resolution (SR) approach based on the use of Generative Adversarial Network (GAN) models for image processing, as an alternative to traditional methods to achieve higher resolution images, hence, remote sensing applications could take advantage of this new information and improve its outcomes. We used two datasets to train and validate our approach, the first composed by images from the DIV2K open access dataset and the second by images from Sentinel-2 satellite. The experimental results are based on the comparison of the similarity between the Landsat-8 images obtained by the super resolution processing by our approach (for both datasets), against its corresponding reference from Sentinel-2 satellite image, computing the Peak Signal-to-Noise Ratio (PSNR) and the Structural Similarity (SSIM) as metrics for this purpose. In addition, we present a visual report in order to compare the performance of each trained model, analysis that shows interesting improvements of the resolution of Landsat-8 satellite images.

Idioma originalInglés
Título de la publicación alojadaInformation Management and Big Data - 6th International Conference, SIMBig 2019, Proceedings
EditoresJuan Antonio Lossio-Ventura, Nelly Condori-Fernandez, Jorge Carlos Valverde-Rebaza
EditorialSpringer
Páginas291-298
Número de páginas8
ISBN (versión impresa)9783030461393
DOI
EstadoPublicada - 2020
Evento6th International Conference on Information Management and Big Data, SIMBig 2019 - Lima, Perú
Duración: 21 ago. 201923 ago. 2019

Serie de la publicación

NombreCommunications in Computer and Information Science
Volumen1070 CCIS
ISSN (versión impresa)1865-0929
ISSN (versión digital)1865-0937

Conferencia

Conferencia6th International Conference on Information Management and Big Data, SIMBig 2019
País/TerritorioPerú
CiudadLima
Período21/08/1923/08/19

Huella

Profundice en los temas de investigación de 'Super Resolution Approach Using Generative Adversarial Network Models for Improving Satellite Image Resolution'. En conjunto forman una huella única.

Citar esto