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

Claudia Paris; Jose Bioucas-Dias; Lorenzo Bruzzone

doi:10.1109/IGARSS.2017.8127525

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 proceeding › Conference contribution › Academic › peer-review

10 Citations (Scopus)

Abstract

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 language	Undefined
Title of host publication	2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Subtitle of host publication	Proceedings
Publisher	IEEE
Pages	2589-2592
Number of pages	4
ISBN (Electronic)	978-1-5090-4951-6, 978-1-5090-4950-9
ISBN (Print)	978-1-5090-4952-3
DOIs	https://doi.org/10.1109/IGARSS.2017.8127525
Publication status	Published - 4 Dec 2017
Externally published	Yes
Event	37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017 - Fort Worth Convention Center, Fort Worth, United States Duration: 23 Jul 2017 → 28 Jul 2017 Conference number: 37

Publication series

Name
ISSN (Electronic)	2153-7003

Conference

Conference	37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017
Abbreviated title	IGARSS 2017
Country/Territory	United States
City	Fort Worth
Period	23/07/17 → 28/07/17

Access to Document

10.1109/IGARSS.2017.8127525

Cite this

@inproceedings{6f86a402df9c4e83a929f3bf76e8d3a2,

title = "A hierarchical approach to superresolution of multispectral images with different spatial resolutions",

abstract = "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.",

author = "Claudia Paris and Jose Bioucas-Dias and Lorenzo Bruzzone",

year = "2017",

month = dec,

day = "4",

doi = "10.1109/IGARSS.2017.8127525",

language = "Undefined",

isbn = "978-1-5090-4952-3",

publisher = "IEEE",

pages = "2589--2592",

booktitle = "2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)",

address = "United States",

note = "37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017 ; Conference date: 23-07-2017 Through 28-07-2017",

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Paris, C, Bioucas-Dias, J & Bruzzone, L 2017, A hierarchical approach to superresolution of multispectral images with different spatial resolutions. in 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS): Proceedings., 8127525, IEEE, pp. 2589-2592, 37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017, Fort Worth, Texas, United States, 23/07/17. https://doi.org/10.1109/IGARSS.2017.8127525

A hierarchical approach to superresolution of multispectral images with different spatial resolutions. / Paris, Claudia; Bioucas-Dias, Jose; Bruzzone, Lorenzo.
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS): Proceedings. IEEE, 2017. p. 2589-2592 8127525.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - Bioucas-Dias, Jose

AU - Bruzzone, Lorenzo

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PY - 2017/12/4

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N2 - 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.

AB - 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.

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