Doctoral Dissertation, University of California, San Diego, 2014.
With modern optimization techniques it is generally possible to
form some kind of image estimate using an arbitrary collection of
views or sensor measurements of an unknown object. The question is
what is the best result that one can get with that data and will it
be acceptable? We use optimization theory to analyze inverse
problems such as this and formulate strategies for understanding
how much high resolution information is contained in the data and
how to intelligently reconstruct the best image possible.
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