Wavelet domain blur invariants for 1D discrete signals

Authors:
Iman Makaremi;Karl Leboeuf;Majid Ahmadi
Affiliations:
Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada;Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada;Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada
Venue:
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I
Year:
2011

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Abstract

Wavelet domain blur invariants, which were proposed for the first time in [10] by the authors, are modified in order to suit a wider range of applications. With the modified blur invariants, it is possible to address the applications in which the blur systems are not necessarily energy-preserving. Also, for a simpler implementation of the wavelet decomposition for discrete signals, we use a method which preserves an important property of the invariants: shift invariance. The modified invariants are utilized in two different experiments in order to evaluate their performance.