title: Coded aperture spectroscopy with denoising through sparsity.
abstract: We compare noise and classification metrics for three aperture codes in dispersive spectroscopy. In contrast with previous theory, we show that multiplex codes may be advantageous even in systems dominated by Poisson noise. Furthermore, ill-conditioned codes with a regularized estimation strategy are shown to perform competitively with well-conditioned codes.
authors.affiliation: Duke Imaging and Spectroscopy Program, Duke University Electrical Engineering Dept, PO Box 90291, Durham, NC 27708, USA.
authors.forename: Alex
authors.initials: A
authors.lastname: Mrozack
authors.forename: Daniel L
authors.initials: DL
authors.lastname: Marks
authors.forename: David J
authors.initials: DJ
authors.lastname: Brady
mesh_terms: D016477:Artifacts; D003198:Computer Simulation; D044962:Data Compression / Q000379:methods*; D008027:Light; D008962:Models, Theoretical; D012542:Scattering, Radiation; D059629:Signal-To-Noise Ratio; D013057:Spectrum Analysis / Q000379:methods*