Blind restoration of images degraded by space-variant blurs using iterative algorithms for both blur identification and image restoration

The spherical aberration in the primary mirror of the Hubble Space Telescope causes more than 80% of the light from a point source to be spread into a halo of radius of 2–3 arcsec. The point spread function (PSF) is both time variant (resulting from spacecraft jitter and desorption of the secondary mirror support structure) and space variant (owing to the Cassegrain repeater optics in the Wide Field / Planetary Camera). A variety of image restoration algorithms have been utilized on HST data with some success, although optimal restorations require better modeling of the PSF and the development of efficient restoration algorithms that accommodate a spacevariant PSF. The first HST servicing mission (December 1993) will deploy a corrective optics system for the Faint Object Camera and the two spectrographs and a second generation WF/PC with internal corrective optics. As simulations demonstrate, however, the restoration algorithms developed now for aberrated images will be very useful for removing the remaining diffraction features and optimizing dynamic range in post-servicing mission data.

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Fast Weighted Total Variation Regularization Algorithm for Blur Identification and Image Restoration

IEEE Access ◽

10.1109/access.2016.2516949 ◽

2016 ◽

Vol 4 ◽

pp. 6792-6801 ◽

Cited By ~ 9

Author(s):

Haiying Liu ◽

Jason Gu ◽

Max Q.-H. Meng ◽

Wu-Sheng Lu

Keyword(s):

Image Restoration ◽

Total Variation ◽

Total Variation Regularization ◽

Regularization Algorithm ◽

Blur Identification ◽

Weighted Total Variation ◽

Weighted Total Variation Regularization

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Nonlinear locally adaptive and iterative algorithms of image restoration

Journal of Electronic Imaging ◽

10.1117/12.276851 ◽

1997 ◽

Vol 6 (4) ◽

pp. 439

Author(s):

Vladimir P. Melnik

Keyword(s):

Image Restoration ◽

Iterative Algorithms ◽

Locally Adaptive

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Research on Realization of Medical Image Restoration Based on Blind Equalization Algorithm

Journal of Medical Imaging and Health Informatics ◽

10.1166/jmihi.2020.2935 ◽

2020 ◽

Vol 10 (4) ◽

pp. 809-813

Author(s):

Ting Han ◽

Ruo-Han Zhao ◽

Mo Dong

Keyword(s):

Image Restoration ◽

Medical Image ◽

Medical Images ◽

Blind Equalization ◽

Diagnostic Errors ◽

Degradation Process ◽

Restoration Algorithm ◽

Equalization Algorithm ◽

Improvement Effect ◽

Blind Restoration

In order to study the realization of medical image restoration, this study mainly adopts blind equalization algorithm to analyze medical images, and observes the improvement effect of blind equalization technology on medical images. In the process of medical image formation, it is unavoidable to be affected by point spread function, which leads to image degradation and brings great difficulties to diagnosis, and the results of degradation are often unpredictable. The results show that the blind restoration algorithm can restore the image when the degradation process of the medical image is uncertain, which makes the medical image clearer and more accurate, brings great convenience to the diagnosis, and also reduces the diagnostic errors caused by the unclear image.

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