Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Blind data restoration with an extracted filter function

Not Accessible

Your library or personal account may give you access

Abstract

A method for performing blind deconvolutions on degraded images and data has been developed. The technique uses a power law relation applied to the Fourier transform of the degraded data to extract a filter function. This filter function closely resembles the point-spread function of the system and can be used to restore and enhance higher-frequency content. The process is noniterative and requires only that the point-spread function be space invariant and the transfer function be real. The algorithm has been validated by direct comparisons by use of a pseudoinverse filter with known transfer functions.

© 2001 Optical Society of America

Full Article  |  PDF Article
More Like This
Noniterative blind data restoration by use of an extracted filter function

James N. Caron, Nader M. Namazi, and Chris J. Rollins
Appl. Opt. 41(32) 6884-6889 (2002)

Self-deconvolution for shift-and-add imaging

Yoshifumi Sudo and Naoshi Baba
Opt. Lett. 30(11) 1309-1311 (2005)

Rapid supersampling of multiframe sequences by use of blind deconvolution

James N. Caron
Opt. Lett. 29(17) 1986-1988 (2004)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (3)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Equations (10)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.