6533b7d4fe1ef96bd1263054
RESEARCH PRODUCT
Demultiplexing Visible and Near-Infrared Information in Single-Sensor Multispectral Imaging
Jean-baptiste ThomasZahra SadeghipoorSabine Süsstrunksubject
Mean squared errorComputer sciencebusiness.industryElectromagnetic spectrum010401 analytical chemistryMultispectral imageNear-infrared spectroscopy02 engineering and technologyFilter (signal processing)01 natural sciencesSample (graphics)0104 chemical sciencesMultispectral pattern recognitionOptics0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingbusinessVisible spectrumRemote sensingdescription
In this paper, we study a single-sensor imaging system that uses a multispectral filter array to spectrally sample the scene. Our system captures information in both visible and near-infrared bands of the electromagnetic spectrum. Due to manufacturing limitations, the visible filters in this system also transmit the NIR radiation. Similarly, visible light is transmitted by the NIR filter, leading to inaccurate mixed spectral measurements. We present an algorithm that resolves this issue by separating NIR and visible information. Our method achieves this goal by exploiting the correlation of multispectral images in both spatial and spectral domains. Simulation results show that the mean square error of the data corrected by our method is less than 1/20 of the error in sensor spectral measurements.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2016-11-07 | Color and Imaging Conference |