Hyperspectral Tomography Sensors

Tomography is a powerful technique to obtain imaging measurement by line-of-sight- averaged projections. Tomography is a mature technique practice in many fields, to name a few, medicine, archeology, material science etc.

However, established tomographic techniques usually require many projections. For instance, a typical medical CT (computerized tomography) exam of our teeth uses tens of thousands of projections taken at different angles. Such requirement is problematic when the phenomena under investigation are transient or the cost to obtain projections is high. Imaging of fuel and temperature distribution in an internal combustion engine exemplifies both issues.

In this research, we seek creative methods to significantly reduce the number of projections required for satisfactory tomographic imaging. The figure below illustrates the concept. The technique, named hyperspectral tomography, uses advanced lasers to scan absorption spectra at rapid rate at multiple locations. Novel inversion algorithms then retrieve critical flow information (e.g., temperature and concentration of chemical species) from the measured spectra with both spatial and temporal resolution.

2009-gordon-research-conference-poster.pdf 2009 Gordon Research Conference poster on hyperspectral tomography (PDF | 1MB)
hyperspectral-tomography-presentation.pdf Hyperspectral Tomography Presentation (PDF | 976KB)

Relevant Publications:

1. Ma, L., and Cai, W.
Development of a hyperspectral tomography sensor for practical propulsion devices.
Paper number AIAA 2008-4782; Presented at the 44th AIAA/ASME/SAE/ASEE  Joint Propulsion Conference & Exhibit, Hartford, CT, July 21-23, 2008.

2. Ma, L., and Cai, W.
Numerical investigation of hyperspectral tomography for simultaneous temperature and concentration imaging.
Applied Optics 47 (21): 3751-3759, 2008

 3. Ma, L., and Cai, W.
Determination of the optimal regularization parameters in hyperspectral tomography.
Applied Optics 47 (23); 4186, 2008

4. Cai, W., Ewing, D.J. and Ma, L.
Application of simulated annealing for multispectral tomography.
Computer Physics Communications 179; 250-255, 2008