A New Optimized Denoising Method applied to the Spot World Heritage Initiative and its Spot 5 Supermode images

Antoine Masse (1) , Christophe Latry (1) , Julien Nosavan (1) , Simon Baillarin (1) , Sébastien Lefèvre (2)

1 CNES - Centre National d'Études Spatiales [Toulouse]
2 OBELIX - Environment observation with complex imagery

In the context of the Spot World Heritage (SWH) initiative, the long term archive of Spot 1 to 5 satellite data will be reprocessed. This initiative gives the opportunity to increase Spot data quality and production efficiency with the introduction of new state-of-the-art processing methods. In this context, we consider the Spot 5 Supermode processing chain and the introduction of a new denoising method. Our objective is to propose the best denoising method in terms of efficiency and accuracy for the Spot 5 Supermode data production. We report two experimentations that lead to the choice of the Non Local Bayes (NLB) denoising method; it is fast, accurate and remains stable in terms of efficiency and quality for different landscapes and image sizes. We also introduce two optimized versions of the NLB algorithm that increase the computation efficiency by a factor up to 4.

Mots clés: Index Terms-Spot World Heritage; Spot; Supermode; Restoration; Denoising; Non Local Bayes

Domaines: Traitement des images [eess.IV]

Antoine Masse, Christophe Latry, Julien Nosavan, Simon Baillarin, Sébastien Lefèvre. A New Optimized Denoising Method applied to the Spot World Heritage Initiative and its Spot 5 Supermode images. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018, Valencia, Spain. ⟨10.1109/IGARSS.2018.8518357⟩. ⟨hal-01969010⟩