Enhancing the Spatial Resolution of Sentinel 3 Synergy Through the Super-Resolution via Repeated Refinement Method

EasyChair Preprint 11012

Abstract

Despite the abundance of open Earth Observation (EO) data from the Copernicus program and the GEOSS platform, their uptake in the context of Climate Change (CC) related applications is often limited due to inherent spatial and temporal resolution constraints. Super-resolution techniques aim to reconstruct high spatial resolution images from degraded low spatial resolution images, but current approaches are being tested mainly for high spatial resolution imagery and small scaling factors. To fill this gap, this study investigates the ability of the diffusion-based image super-resolution via repeated refinement (SR3) method in enhancing the spatial resolution of the near-daily Sentinel-3 SYNERGY images from 300 to 75 meters by taking advantage of the higher spatial resolution of the Sentinel-2 MSI images during model training. In quantitative and qualitative evaluations of results, SR3 provides convincing results and reveals its suitability in spatially enhancing Sentinel-3 SYNERGY images.

Keyphrases: Sentinel-3 SYNERGY, diffusion model, large scaling factor, super-resolution

@booklet{EasyChair:11012,
  author    = {Maria Dekavalla and Dimitris Bliziotis and Valantis Tsiakos and Georgios Tsimiklis and Angelos Amditis},
  title     = {Enhancing the Spatial Resolution of Sentinel 3 Synergy Through the Super-Resolution via Repeated Refinement Method},
  howpublished = {EasyChair Preprint 11012},
  year      = {EasyChair, 2023}}