Data Transformation for Super-Resolution on Ocean Remote Sensing Images - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2022

Data Transformation for Super-Resolution on Ocean Remote Sensing Images

Résumé

High-resolution ocean remote sensing imaging is of vital importance for research in the field of ocean remote sensing. However, the available ocean remote sensing images are often averaged data, whose resolution is lower than the instant remote sensing images. In this paper, we propose a data transformation method to process remote sensing images in different locations and resolutions. We target satellite-derived sea surface temperature (SST) images as a specific case-study. In detail, we use a modified very deep super-resolution (VDSR) model as our baseline model and propose a data transformation method to improve the robustness of the model. Furthermore, we also illustrates how the degree of difference in the data distribution influences the model’s robustness and also, how our proposed data transformation method can improve the model’s robustness. Experiment results prove that our method is effective and our model is robust.
Fichier sous embargo
Fichier sous embargo
0 5 14
Année Mois Jours
Avant la publication
mercredi 1 janvier 2025
Fichier sous embargo
mercredi 1 janvier 2025
Connectez-vous pour demander l'accès au fichier

Dates et versions

hal-04178752 , version 1 (08-08-2023)

Licence

Identifiants

Citer

Yuting Yang, Kin-Man Lam, Xin Sun, Junyu Dong, Muwei Jian, et al.. Data Transformation for Super-Resolution on Ocean Remote Sensing Images. 12th International Conference on Intelligent Information Processing (IIP), May 2022, Qingdao, China. pp.431-443, ⟨10.1007/978-3-031-03948-5_35⟩. ⟨hal-04178752⟩
13 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More