Results 241 to 250 of about 11,800,567 (295)

Self-supervised image restoration in coherent X-ray neuronal microscopy

Laugros A, Cloetens P, Bosch C, Schoonhoven R, Pavlovic L, Kuan AT, Livingstone J, Zhang Y, Kim M, Hendriksen A, Holler M, Wanner AA, Azevedo A, Batenburg KJ, Tuthill JC, Lee WA, Schaefer AT, Vigano N, Pacureanu A.   +18 more
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Digital image restoration

IEEE Signal Processing Magazine, 1997
Mark R. Banham, Aggelos K. Katsaggelos
exaly   +2 more sources

Nonlocally Centralized Sparse Representation for Image Restoration [PDF]

IEEE Transactions on Image Processing, 2013
Sparse representation models code an image patch as a linear combination of a few atoms chosen out from an over-complete dictionary, and they have shown promising results in various image restoration applications.
Weisheng Dong
exaly   +2 more sources

Restoration of longitudinal Images

Annual Meeting Optical Society of America, 1987
A method of restoring longitudinal details in ordinary images is presented. By using a transfer theory for longitudinal objects and inverse filtering, the longitudinal image may be restored. The usual Fourier theory and sampling theorems for transverse images cannot be used directly in the longitudinal case.
Y, Hu, B R, Frieden
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Iterative Image Restoration

Applied Optics, 1975
The projection method of solving a set of linear equations was used to restore linearly degraded images. The advantages of this method are that it always converges, it can readily make use of a priori information about the image, and it does not need excessive computation time.
T S, Huang, D A, Barker, S P, Berger
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Turbo image restoration

Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings., 2003
A new iterative processing for image restoration is proposed based on the turbo iterative principle. For this purpose, two uncorrelated component images issued from an original image are differently filtered and the pieces of information extracted from both filters are mutually exchanged in the iterative process.
Hong Sun, Henri Maître, Bao Guan
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On multiresolution image restoration

Proceedings of the 12th IAPR International Conference on Pattern Recognition (Cat. No.94CH3440-5), 2002
This paper argues that the correct way to use a multiresolution approach to image restoration is to coarsen the posterior distribution of the image via the renormalization group transformation (RGT). It summarises the main results on RGT and points out the difficulties with it.
G. Nicholls, Maria Petrou
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Binary‐image restoration

Canadian Journal of Statistics, 1994
AbstractWe consider the problem of binary‐image restoration. The image being restored is not random, and we make no assumption about the nature of its contents. The estimate of the colour at each site is a fixed (the same for all sites) function of the data available in a neighbourhood of that site.
Meloche, J., Zamar, R. H.
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An image restoration by fusion

Pattern Recognition, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Image restoration in computed tomography: restoration of experimental CT images

IEEE Transactions on Medical Imaging, 1992
It is pointed out that to restore experimental computed tomography (CT) images which have been blurred by a spatially variant point spread function (PSF), a quadrant symmetry method which simultaneously optimizes storage requirements for the estimated PSFs and computational speed is used.
Satyapal Rathee, Zoly J. Koles, Thomas R. Overton   +2 more
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