Bayesian-Based Iterative Method of Image Restoration

By W. Richardson. 1972

Subfields: Computer Vision and Pattern Recognition, Probabilistic & Bayesian Methods

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Citations in the corpus

Generative Adversarial Networks recover features in astrophysical images of galaxies beyond the deconvolution limit (2017, background): “MNRASL 467, L110–L114 (2017) D ow nloaded from https://academ ic.oup.com /m nrasl/article-abstract/467/1/L110/2931732 by guest on 18 February 2020 (Richardson 1972; Lucy 1974)3 achieves a PSNR of 18.7 dB.”
Algorithms for Nonnegative Matrix Factorization with the β-Divergence (2010, methodology): “These algorithms are the Iterative Space Re-constructing Algorithm (ISRA) of Daube-Witherspoon and Muehllehner (1986) and the Richardson-Lucy (RL) algorithm of Richardson (1972); Lucy (1974), which perform nonnegative linear regression with the Euclidean distance and KL divergence, respectively.”
Single Image Deblurring Using Motion Density Functions (2010, background): “In most recent work, image blur is modeled as the convolution of an unobserved latent image with a single, spatially invariant blur kernel [1,2,3,4,5,6,7,8,9,10,11].”
Coded exposure photography: motion deblurring using fluttered shutter (2006, methodology): “A well-known class of techniques follow the RichardsonLucy algorithm [Richardson 1972][Lucy 1974] which uses a statistical model for image formation and is based on the Bayes formula.”
Mapping the three-dimensional density of the galactic bulge with VVV red clump stars (2013, background): “(8) c© 2012 RAS, MNRAS 000, 1–14 Provided Lucy-Richardson deconvolution (Richardson 1972; Lucy 1974) converges, it converges to the maximum likelihood deconvolution for Poisson distributed errors, and is therefore an appropriate choice (Shepp & Vardi 1982).”
Early SPI/INTEGRAL constraints on the morphology of the 511 keV line emission in the 4th galactic quadrant (2003, methodology): “For this purpose, we employed in this work the RichardsonLucy algorithm (Richardson 1972, Lucy 1974) that has been successfully applied to γ-ray data of earlier missions (e.g. Knödlseder et al. 1999; Milne et al. 2000).”
Size–strain line-broadening analysis of the ceria round-robin sample (2004, unknown): “We instead used a Bayesian deconvolution following the Richardson algorithm3 (Richardson, 1972; Kennett et al., 1978).”
Iterative reconstruction techniques in emission computed tomography (2006, background): “It is also interesting to note that the same update equation (32) (without ri and si) was earlier developed for restoration of astronomy images without explicit recourse to either the EM algorithm or functional substitution methodology (Richardson 1972, Lucy 1974).”
Non-uniform Deblurring for Shaken Images (2010, methodology): “One method frequently used for deconvolution is the Richardson-Lucy algorithm [14] [21].”
Learning Deep CNN Denoiser Prior for Image Restoration (2017, background): “Image restoration (IR) has been a long-standing problem for its highly practical value in various low-level vision applications [1, 9, 47].”
Theory and Use of the EM Algorithm (2011, background): “Another notable instance of a special case of the EM algorithm is the Richardson–Lucy image deconvolution of the early 1970s [51, 33].”
Removing Camera Shake from a Single Photograph (2009, methodology): “Consequently, we reconstruct the latent color image L with the Richardson-Lucy (RL) algorithm [Richardson 1972; Lucy 1974].”
Optical Imaging and Spectroscopy (2009, methodology): “Rogalski [210], # 2003 Elsevier Limited.”
Fast removal of non-uniform camera shake (2011, background): “, Richardson [18] and Lucy [13], which date back to the early 70s.”