Journal
2020 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
Volume -, Issue -, Pages 2855-2859Publisher
IEEE
Keywords
hyperspectral pansharpening; compressed sensing; primal-dual splitting
Categories
Funding
- JST CREST [JPMJCR1662, JPMJCR1666]
- JSPS KAKENHI [18J20290, 18H05413]
- Grants-in-Aid for Scientific Research [18J20290, 18H05413] Funding Source: KAKEN
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Hyperspectral (HS) imaging based on compressed sensing (CS) is actively studied to capture an HS image in one shot. Although CS can reconstruct an HS image from a much less number of random observations, capturing an HS image of high spatial and spectral resolution (HR-HS image) is still difficult because of current imaging systems. In this paper, we propose a new methodology of HS imaging, named compressed HS pansharpening. Specifically, the concept enables to generate an HR-HS image from a compressively-sensed observation with the help of a panchromatic (PAN) image. For a realistic setting, the concept assumes that both a CS observation and a PAN image are contaminated by noise. Then, an HR-HS and a clean PAN image are simultaneously estimated from the noisy pair by solving a newly-formulated optimization problem. In the experiments, we demonstrate the utility of our proposed methodology.
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