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Appl Opt. 2008 Aug 10;47(23):4186-92.

Determination of the optimal regularization parameters in hyperspectral tomography.

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  • 1Department of Mechanical Engineering, Clemson University, Clemson, South Carolina, 29634-0921, USA.


In a previous paper, we described a novel technique to exploit hyperspectral absorption spectroscopy to retrieve tomographic imaging of temperature and species concentration simultaneously. This technique casts the tomographic inversion into a nonlinear minimization problem with regularizations. Here a simple and effective method is developed to determine the optimal regularization parameters in the nonlinear optimization problem. This method, combined with the minimization method described previously, provides a robust algorithm for hyperspectral tomography. This method takes advantage of an inherent feature of absorption and is therefore expected to be useful for other sensing techniques based on absorption spectroscopy.

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