Practical Spectral Photography Ralf Habel1 Michael Kudenov2 Michael Wimmer1 Institute of Computer Graphics and Algorithms Vienna University of Technology1 Optical Detection Lab University of Arizona2

Motivation Spectroscopy is most important analysis tool in all natural sciences Astrophysics, chemical/material sciences, biomedicine, geophysics,… Industry applications: Mining, airborne sensing, QA,… In computer graphics: Colors Material reflectance Spectral/predictive rendering … Ralf Habel

Spectral Imaging Records image at narrow wavelength bands In visible range not only RGB (3 channels) but many more (6-400 channels) Result: 3D data cube 2 spatial image axis 1 wavelength axis Ralf Habel

Spectral Imaging Usually done with highly specialized devices Many methods to build devices Scanning slits, rotating mirrors, special sensor, filters, prisms, … Usually scan along one of the data cube axis All very costly due to opto-mechanical components “Simplest” spectral imager: Camera + band filters Requires switching of filters Limited in number of bands Ralf Habel

Motivation Why not use consumer cameras and equipment for spectral imaging? High quality, very sensitive Highly accurate lenses Practical Constraints: No camera modification No lab/desktop/optical bench setup No expensive components Ralf Habel

CTIS Principle Computed Tomography Image Spectrometer Diffraction grating parallel-projects 3D data cube in different directions on image plane (sensor): Ralf Habel

CTIS Principle Computed Tomography Image Spectrometer Diffraction grating parallel-projects 3D data cube in different directions on image plane (sensor): Ralf Habel

CTIS Principle Sensor records projections of 3D data cube All information needed is recorded in one image “Snapshot” spectrometry Challenge is to reconstruct 3D data cube from projections Tomographic rec. with Expectation Maximization More details in paper Ralf Habel

CTIS Optical Path Imaging lens + square/slit aperture creates virtual image Ralf Habel

CTIS Optical Path Imaging lens + square/slit aperture creates virtual image Collimating lens makes light parallel Ralf Habel

CTIS Optical Path Imaging lens + square/slit aperture creates virtual image Collimating lens makes light parallel Diffraction grating creates projections Ralf Habel

CTIS Optical Path Imaging lens + square/slit aperture creates virtual image Collimating lens makes light parallel Diffraction grating creates projections Re-imaging lens focuses on sensor Ralf Habel

CTIS Optical Path Imaging lens + square/slit aperture creates virtual image Collimating lens makes light parallel Diffraction grating creates projections Re-imaging lens focuses on sensor Ralf Habel

CTIS Optical Path Built with: Drain pipe & duct tape 50mm, 17-40mm and macro lens Diffraction gel ($2 per sheet) in gel holder Ralf Habel

CTIS Camera Objective Ralf Habel

CTIS Camera Objective Ralf Habel

HDR Image Acquisition No overexposed pixels allowed Projections (diffractions) weaker than center image Avoids noisy signal where camera response is weak Ralf Habel

Spatial Wavelength Calibration Mapping from 3D data cube into projections Laser pointers (red, green and blue) with known wavelengths shot through a diffusor and pinhole Monochromatic point light source Pictures of pinhole give mapping of one voxel in 3D data cube All other projections values interpolated/extrapolated Ralf Habel

CTIS Principle Ralf Habel

Spatial Wavelength Calibration Ralf Habel

Spectral Response Calibration Spectral response of the diffraction grating + RGB sensor for red, green and blue Picture of light source with continuous known spectrum We use calibrated halogen lamp Ralf Habel

Spectral Photography Results Take HDR picture with CTIS camera objective Reconstruct 3D data cube for red, green and blue image color channels Mapping from spatial calibration Combine RGB spectral response of each pixel to true spectrum with spectral de-mosaicking Mapping from spectral response calibration Ralf Habel

Spectral Photography Results Protoype data cube resolutions: 120x120 pixels 4.59 nm (54 channels) Accuracy reduced in high blue and low reds due to color filters Slight Expectation Maximization reconstruction artifacts Nowhere near possible optimum! Ralf Habel

Spectral Photography Results Ralf Habel

Spectral Photography Results Ralf Habel

Future Better CTIS objective Increase data cube resolution/accuracy: Drain pipes and duct tape have their limits… Optimized optical path and components More compact/integrated device Increase data cube resolution/accuracy: Structured aperture Digital holography – form diffraction/projections in any way Better solutions to tomographic reconstruction Is active research in optics No vision based approach yet! Ralf Habel

Future Turning mobile devices into spectrometers - consumer spectroscopy? 8 MP high sensitivity sensors HDR capabilities Very low cost! “Snapshot” capability: Spectral movies with consumer cameras? Not only good for computer graphics: Blood sample analysis Water contamination analysis As part of a TricorderTM Ralf Habel

Practical Spectral Photography Thank You! Ralf Habel