Blind Image Deconvolution

By P. Laplante. 2001

663 citations recorded by the source corpus.

How researchers see this paper

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Fast and robust multiframe super resolution (2004, methodology): “Although many single-frame blind deconvolution algorithms have been suggested in the last 30 years [ 28 ] and recently [12] incorporated a single-parameter blur identification algorithm in their super-resolution method, still there is need”
Advances and challenges in super‐resolution (2004, background): “tion algorithms have been suggested in the last 30 years [ 26 ], and recently [31] incorporated”
Image and depth from a conventional camera with a coded aperture (2007, background): “This is closely related to the blind deconvolution problem [Kundur and Hatzinakos 1996].”
Perceptual visual quality metrics: A survey (2011, methodology): “In the cases with only a test image available, various blind methods to measure the blur/sharpness in an image have been proposed with edge spread detection [100,120], kurtosis [16,201], frequency domain analysis [78,98], PSF estimation [190], width/amplitude of lines and edges [35], and local contr”
Deep Video Deblurring for Hand-Held Cameras (2017, background): “Modern single-image deblurring approaches jointly estimate a blurring kernel (either single or spatially varying) and the underlying sharp image via deconvolution [23].”
Blind deconvolution in scientific imaging & computational photography (2011, methodology): “See (Kundur and Hatzinakos, 1996) for an overview of related methods.”