Physically motivated correlation formalism in hyperspectral imaging
Document Type
Conference Proceeding
Publication Date
12-1-2004
Abstract
Most remote sensing data-sets contain a limiting number of independent spatial and spectral measurements, beyond which no effective increase in information is achieved. This paper presents a Physically Motivated Correlation Formalism (PMCF),which places both Spatial and Spectral data on an equivalent mathematical footing in the context of a specific Kernel, such that, optimal combinations of independent data can be selected from the entire Hypercube via the method of 'Correlation Moments'. We present an experimental and computational analysis of Hyperspectral data sets using the Michigan Tech VFTHSI [Visible Fourier Transform Hyperspectral Imager] based on a Sagnac Interferometer, adjusted to obtain high SNR levels. The captured Signal Interferograms of different targets - aerial snaps of Houghton and lab-based data (white light, He-Ne laser, discharge tube sources) with the provision of customized scan of targets with the same exposures are processed using inverse imaging transformations and filtering techniques to obtain the Spectral profiles and generate Hypercubes to compute Spectral/Spatial/Cross Moments. PMCF answers the question of how optimally the entire hypercube should be sampled and finds how many spatial-spectral pixels are required for a particular target recognition.
Publication Title
Proceedings of SPIE - The International Society for Optical Engineering
Recommended Citation
Roy, A.,
&
Rafert, J.
(2004).
Physically motivated correlation formalism in hyperspectral imaging.
Proceedings of SPIE - The International Society for Optical Engineering,
5298, 188-199.
http://doi.org/10.1117/12.531943
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/12114