SWIR Imaging and Echelle Spectroscopy via Compressive Sensing
Kelly, Kevin F.
Master of Science
A new sampling theory, called compressive sensing (CS), has recently emerged and its fundamental idea can be distilled as: it is possible to obtain near complete recovery of a signal/image from a small set of mixed measurements of it if the signal/image possesses properties akin to sparseness. Based on this theory, we have developed a unique hardware platform for imaging and spectroscopy applications which incorporates a spatial modulator and a single pixel detector. Random projections of the signal/image are applied to the light modulator and the modulated light is focused on the single detector generating a series of photovoltage values which are later used in the image reconstruction. For wavelengths outside the visible spectrum, where it is especially expensive to produce the large detector arrays, this scheme provides a far better solution using a single detector element.
Applied sciences; Electrical engineering