SPECTRAL DEMULTIPLEXED IMAGING
The simultaneous capture of imaging data at multiple wavelengths across the electromagnetic spectrum is highly challenging, requiring complex and costly multispectral image devices. We introduce a new form of computational multispectral imaging called spectral demultiplexed imaging (SDI), where single-shot multispectral imaging using conventional image sensors with color filter arrays is achieved via a novel numerical spectral demultiplexer that demultiplexes broadband image sensor measurements into a large set of narrowband images at a multitude of spectral wavelengths. To illustrate the effectiveness of SDI, we constructed a compact field-portable computational multispectral microscopy system powered by an integrated Raspberry Pi computer and a Raspberry Pi camera module. The computational multispectral microscopy system was demonstrated to produce narrowband microscopy images at 16 different wavelengths with a single acquisition without the need for wavelength scanning, which makes it well-suited for fast microscopy imaging applications such as the study of transient phenomenona.
For more information on the SDI, please read:
1. J. Deglint, F. Kazemzadeh, D. Cho, D. Clausi, and A. Wong, Numerical Demultiplexing of Color Image Sensor Measurements via Non-linear Random Forest Modeling. Nature Scientific Reports, 2016.
2. J. Deglint, F. Kazemzadeh, A. Wong, and D. Clausi, Photoplethysmographic imaging via spectrally demultiplexed erythema fluctuation analysis for remote heart rate monitoring. in the proceedings of SPIE Photonics West, 2015.
3. J. Deglint, F. Kazemzadeh, A. Wong, and D. Clausi, Numerical Spectral Demulitplexing Microscopy of Measurements from an Anatomical Specimen. Journal of Computational Vision and Imaging Systems, 2015.
4. F. Kazemzadeh, M. Shafiee, J. Deglint, E. Li, A. Wong, I. Khodadadzadeh, and S. Saini, In-Situ Virtual Spectral Multiplexing Imaging Microscopy of Transient Phenomena, in the proceedings of SPIE Photonics and Optics, 2015.
5. J. Deglint, F. Kazemzadeh, A. Wong, and D.A. Clausi, Inference of Dense Spectral Reflectance Images from Sparse Reflectance Measurement Using Non-Linear Regression Modeling, in the proceedings of SPIE Optics and Photonics, 2015.
Example images captured of a Helianthus stem using our compact field-portable SDI computational multispectral microscopy system:
The simultaneous capture of imaging data at multiple wavelengths across the electromagnetic spectrum is highly challenging, requiring complex and costly multispectral image devices. We introduce a new form of computational multispectral imaging called spectral demultiplexed imaging (SDI), where single-shot multispectral imaging using conventional image sensors with color filter arrays is achieved via a novel numerical spectral demultiplexer that demultiplexes broadband image sensor measurements into a large set of narrowband images at a multitude of spectral wavelengths. To illustrate the effectiveness of SDI, we constructed a compact field-portable computational multispectral microscopy system powered by an integrated Raspberry Pi computer and a Raspberry Pi camera module. The computational multispectral microscopy system was demonstrated to produce narrowband microscopy images at 16 different wavelengths with a single acquisition without the need for wavelength scanning, which makes it well-suited for fast microscopy imaging applications such as the study of transient phenomenona.
For more information on the SDI, please read:
1. J. Deglint, F. Kazemzadeh, D. Cho, D. Clausi, and A. Wong, Numerical Demultiplexing of Color Image Sensor Measurements via Non-linear Random Forest Modeling. Nature Scientific Reports, 2016.
2. J. Deglint, F. Kazemzadeh, A. Wong, and D. Clausi, Photoplethysmographic imaging via spectrally demultiplexed erythema fluctuation analysis for remote heart rate monitoring. in the proceedings of SPIE Photonics West, 2015.
3. J. Deglint, F. Kazemzadeh, A. Wong, and D. Clausi, Numerical Spectral Demulitplexing Microscopy of Measurements from an Anatomical Specimen. Journal of Computational Vision and Imaging Systems, 2015.
4. F. Kazemzadeh, M. Shafiee, J. Deglint, E. Li, A. Wong, I. Khodadadzadeh, and S. Saini, In-Situ Virtual Spectral Multiplexing Imaging Microscopy of Transient Phenomena, in the proceedings of SPIE Photonics and Optics, 2015.
5. J. Deglint, F. Kazemzadeh, A. Wong, and D.A. Clausi, Inference of Dense Spectral Reflectance Images from Sparse Reflectance Measurement Using Non-Linear Regression Modeling, in the proceedings of SPIE Optics and Photonics, 2015.
Example images captured of a Helianthus stem using our compact field-portable SDI computational multispectral microscopy system: