TR2020-047
Blind Multi-Spectral Image Pan-Sharpening
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- "Blind Multi-Spectral Image Pan-Sharpening", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP40776.2020.9053554, April 2020, pp. 1429-1433.BibTeX TR2020-047 PDF Video
- @inproceedings{Yu2020apr,
- author = {Yu, Lantao and Liu, Dehong and Mansour, Hassan and Boufounos, Petros T. and Ma, Yanting},
- title = {Blind Multi-Spectral Image Pan-Sharpening},
- booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
- year = 2020,
- pages = {1429--1433},
- month = apr,
- publisher = {IEEE},
- doi = {10.1109/ICASSP40776.2020.9053554},
- issn = {2379-190X},
- isbn = {978-1-5090-6631-5},
- url = {https://www.merl.com/publications/TR2020-047}
- }
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- "Blind Multi-Spectral Image Pan-Sharpening", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/ICASSP40776.2020.9053554, April 2020, pp. 1429-1433.
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MERL Contacts:
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Research Areas:
Abstract:
We address the problem of sharpening low spatial-resolution multi-spectral (MS) images with their associated misaligned high spatial-resolution panchromatic (PAN) image, based on priors on the spatial blur kernel and on the cross-channel relationship. In particular, we formulate the blind pan-sharpening problem within a multi-convex optimization framework using total generalized variation for the blur kernel and local Laplacian prior for the crosschannel relationship. The problem is solved by the alternating direction method of multipliers (ADMM), which alternately updates the blur kernel and sharpens intermediate MS images. Numerical experiments demonstrate that our approach is more robust to large misalignment errors and yields better super resolved MS images compared to state-of-the-art optimization-based and deep-learning-based algorithms.
Related News & Events
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NEWS MERL presenting 13 papers and an industry talk at ICASSP 2020 Date: May 4, 2020 - May 8, 2020
Where: Virtual Barcelona
MERL Contacts: Petros T. Boufounos; Chiori Hori; Toshiaki Koike-Akino; Jonathan Le Roux; Dehong Liu; Yanting Ma; Hassan Mansour; Philip V. Orlik; Anthony Vetro; Pu (Perry) Wang; Gordon Wichern
Research Areas: Computational Sensing, Computer Vision, Machine Learning, Signal Processing, Speech & AudioBrief- MERL researchers are presenting 13 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held virtually from May 4-8, 2020. Petros Boufounos is also presenting a talk on the Computational Sensing Revolution in Array Processing (video) in ICASSP’s Industry Track, and Siheng Chen is co-organizing and chairing a special session on a Signal-Processing View of Graph Neural Networks.
Topics to be presented include recent advances in speech recognition, audio processing, scene understanding, computational sensing, array processing, and parameter estimation. Videos for all talks are available on MERL's YouTube channel, with corresponding links in the references below.
This year again, MERL is a sponsor of the conference and will be participating in the Student Job Fair; please join us to learn about our internship program and career opportunities.
ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing. The event attracts more than 2000 participants each year. Originally planned to be held in Barcelona, Spain, ICASSP has moved to a fully virtual setting due to the COVID-19 crisis, with free registration for participants not covering a paper.
- MERL researchers are presenting 13 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held virtually from May 4-8, 2020. Petros Boufounos is also presenting a talk on the Computational Sensing Revolution in Array Processing (video) in ICASSP’s Industry Track, and Siheng Chen is co-organizing and chairing a special session on a Signal-Processing View of Graph Neural Networks.
Related Video
Related Publications
- @article{Yu2022jan,
- author = {Yu, Lantao and Liu, Dehong and Mansour, Hassan and Boufounos, Petros T.},
- title = {Fast and High-Quality Blind Multi-Spectral Image Pansharpening},
- journal = {IEEE Transactions on Geoscience and Remote Sensing},
- year = 2022,
- volume = 60,
- pages = {1--17},
- month = jan,
- doi = {10.1109/TGRS.2021.3091329},
- issn = {1558-0644},
- url = {https://www.merl.com/publications/TR2022-004}
- }