Deblurring images: Matrices, spectra, and filtering

By Jianhong Shen. Mathematics of Computation, 2007

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Single Image Motion Deblurring Using Transparency (2007, background): “The corresponding unblurred opaque object, without motion, completely occludes the background, producing binary alpha values αo where αo ∈ {0, 1}, as shown on the right of Fig.”
Proximal Markov chain Monte Carlo algorithms (2013, background): “…x ∈ R n from a blurred and noisy observed image y ∈ R n related to x by the linear observation model 2 y = H x + w , where H is a linear operator representing the blur point spread function and w is the sample of a zero-mean white Gaussian vector with covariance matrix σ 2 I n (Hansen et al. 2006).”
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems (2009, unknown): “For these experiments we assume reﬂexive (Neumann) boundary conditions [22].”