A General Total Variation Minimization Theorem for Compressed Sensing Based Interior Tomography

Abstract EN

Recently, in the compressed sensing framework we found that a two-dimensional interior region-of-interest (ROI) can be exactly reconstructed via the total variation minimization if the ROI is piecewise constant (Yu and Wang, 2009).

Here we present a general theorem charactering a minimization property for a piecewise constant function defined on a domain in any dimension.

Our major mathematical tool to prove this result is functional analysis without involving the Dirac delta function, which was heuristically used by Yu and Wang (2009).