DocumentCode
1323221
Title
Wavelet-Domain Blur Invariants for Image Analysis
Author
Makaremi, Iman ; Ahmadi, Majid
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of Windsor, Windsor, ON, Canada
Volume
21
Issue
3
fYear
2012
fDate
3/1/2012 12:00:00 AM
Firstpage
996
Lastpage
1006
Abstract
Radiometric degradation is a common problem in the image acquisition part of many applications. There is much research carried out in an effort to deblur such images. However, it has been proven that it is not always necessary to go through a burdensome process of deblurring. To tackle this problem, different blur-invariant descriptors have been proposed so far, which are either in the spatial domain or based on the properties available in the Fourier domain. In this paper, wavelet-domain blur invariants are proposed for the first time for discrete 2-D signals. These descriptors, which are invariant to centrally symmetric blurs, inherit the advantages that this domain provides. It is also proven that the spatial-domain blur invariants are a special version of the proposed invariants. The performance of these invariants will be demonstrated through experiments.
Keywords
Fourier transforms; image restoration; wavelet transforms; Fourier domain; centrally symmetric blurs; discrete 2D signals; image acquisition; image analysis; radiometric degradation; spatial domain; wavelet-domain blur invariants; Convolution; Discrete wavelet transforms; Noise; Wavelet analysis; Wavelet domain; Blur moment invariants; centrally symmetric blur; direct analysis; feature extraction; shift-invariant wavelet transform;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/TIP.2011.2168415
Filename
6021370
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