A hierarchical approach to superresolution of multispectral images with different spatial resolutions

Claudia Paris, Jose Bioucas-Dias, Lorenzo Bruzzone

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

10 Citations (Scopus)


In this paper, we focus the attention on the superresolution of multispectral (MS) multiresolution images (e.g., Sentinel 2, Aster, MODIS). By taking advantage of the high spatial resolution bands, we minimize an objective function containing a quadratic data fitting term, an edge preserving regularizer, and a patch-based plug-and play prior promoting self-similar images. To cope with the ill-posedness of the problem we i) exploit the fact that the images are approximately low-rank, and ii) propose a hierarchical method which sharpens in the first place the medium resolution bands and then the coarse resolution ones. The optimization is solved with the alternating direction method of multipliers (ADMM), yielding a fast, flexible, and effective solver, named Superresolution MUltiband multireSolution Hierarchical approach (SMUSH). Quantitative and qualitative results obtained on simulated and real Sentinel 2 (S2) images show the SMUSH effectiveness.
Original languageUndefined
Title of host publication2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Subtitle of host publicationProceedings
Number of pages4
ISBN (Electronic)978-1-5090-4951-6, 978-1-5090-4950-9
ISBN (Print)978-1-5090-4952-3
Publication statusPublished - 4 Dec 2017
Externally publishedYes
Event37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017 - Fort Worth Convention Center, Fort Worth, United States
Duration: 23 Jul 201728 Jul 2017
Conference number: 37

Publication series

ISSN (Electronic)2153-7003


Conference37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017
Abbreviated titleIGARSS 2017
Country/TerritoryUnited States
CityFort Worth

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