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Superresolution restoration of an image sequence: adaptive filtering approach.

Authors
Type
Published Article
Journal
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Publication Date
Volume
8
Issue
3
Pages
387–395
Identifiers
DOI: 10.1109/83.748893
PMID: 18262881
Source
Medline
License
Unknown

Abstract

This paper presents a new method based on adaptive filtering theory for superresolution restoration of continuous image sequences. The proposed methodology suggests least squares (LS) estimators which adapt in time, based on adaptive filters, least mean squares (LMS) or recursive least squares (RLS). The adaptation enables the treatment of linear space and time-variant blurring and arbitrary motion, both of them assumed known. The proposed new approach is shown to be of relatively low computational requirements. Simulations demonstrating the superresolution restoration algorithms are presented.

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