Active hyperspectral imaging of chemicals on surfaces

Active hyperspectral imaging (HSI) is a promising technique for the detection of chemicals at standoff distances. In active HSI, a target is illuminated by a laser source at many different wavelengths and a camera obtains an image of the illuminated scene at each wavelength. In this research, the feasibility of hyperspectral imaging for the detection of particles on surfaces was demonstrated using potassium chlorate particles on car panels at distances of 5 m, 10 m, and 20 m. Using the Adaptive Cosine Estimation (ACE) algorithm which compares the observed reflectance spectra to a reference spectrum, potassium chlorate fingerprints are easily visible at many different sample angles. However, in general, there is a large amount of variation in the shape and magnitude of spectra in a hyperspectral image that depend on factors such as particle size, viewing geometry, and surface reflectivity. Thus, Mie Theory calculations are performed on simulated materials and combined with information from sources such as Hapke [4], [20] to give qualitative insight into the expected shape and magnitude of reflectance spectra from sparse particles on a surface. The shape of the spectra depends on whether the particles are strongly absorbing or weakly absorbing. Strongly absorbing particles tend to have reflectance maxima near the resonant frequency, whereas weakly absorbing particles tend to have reflectance minima. For highly reflective substrates, the reflectance decreases sharply as the sample angle increases and becomes dominated by backward scattering from the particle which has a flatter spectrum around the Christiansen frequency, the frequency at which the refractive index of the particle is closest to one. The double interaction model, which uses Mie Theory to calculate the contributions to the reflectance along two different light paths, is used to accurately account for how the shape and magnitude of the reflectance spectra of sodium chlorate particles on gold and silica surfaces changes as a function of sample angle and laser angle. A method for approximating the mean particle size based on the location of the peak near the Christiansen frequency is derived. This method, when applied to the sodium chlorate sample, yields a result for the mean particle diameter that is approximately half of the value determined using a microscope. The Hapke Isotropic Multiple Scattering Approximation (IMSA), combined with Mie Theory, is used to give qualitative insight into the expected shape and magnitude of reflectance spectra from bulk powders. Compared with the reflectance spectra from sparse particles, the spectra from bulk powders are much simpler and less dependent on the viewing geometry. The Hapke IMSA model is able to accurately account for the observed changes in the reflectance from bulk sodium chlorate powder at multiple sample angles and laser angles. A final scenario of interest is thin films on rough or porous surfaces. Using a model that takes into account diffusely reflected and specularly reflected light, the observed reflectance spectra from diethyl phthalate (DEP) on a brick is fitted to a high degree of accuracy. This suggests a promising method for using hyperspectral imaging to determine the thickness of liquids on porous surfaces. Finally, the issue of speckle in hyperspectral imaging was examined using simulations based on Fourier optics and information from sources such as Goodman [6], [17]. Speckle is a limiting factor in hyperspectral imaging because it is noise that scales with the signal, and thus cannot be eliminated by increasing the signal strength. Equations from various sources are presented that describe the reduction in speckle contrast for spatial, spectral, polarization, temporal, and angular averaging. Original equations for the reduction in contrast for spectral and angular averaging are derived.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Materials Science and Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2014

Author dc:creator

• Myers, Travis R. (Travis Ray)

Advisor dc:contributor.advisor

• Linn Hobbs.

• Materials Science and Engineering.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/112385

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/112385