Deblurring Images: Matrices, Spectra, and Filtering (Fundamentals of Algorithms 3) (Fundamentals of Algorithms)

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Deep Neural Networks Motivated by Partial Differential Equations (2018, background): “To give an example, assume that K 1 has three input and two output channels and denote by ( · ) a standard convolution operator [21].”
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).”