DocumentCode :
2355642
Title :
A multiresolution approach for video texture registration
Author :
Bonneau, Robert J. ; Novak, Mark E. ; Perretta, James S. ; Ertan, Sevgi
Author_Institution :
AFRL/SNRT, Rome, NY, USA
fYear :
2001
fDate :
1-12 Oct 2001
Firstpage :
126
Lastpage :
128
Abstract :
Electro-optical imagery can have uniform characteristics that prevent it from being registered by conventional edge-based methods. Such uniform characteristics, if they have periodicity, can be exploited using multi-resolution texture extraction techniques. We first use a multi-resolution Markov model to represent electro-optical textures and apply an autoregressive statistical approach to find correspondence between two images. We then demonstrate how this approach reduces the computational complexity of registering of two successive frames of video
Keywords :
Markov processes; autoregressive processes; computational complexity; feature extraction; image registration; autoregressive statistical approach; computational complexity; edge-based methods; electro-optical imagery; multiresolution Markov model; multiresolution approach; multiresolution texture extraction; video texture registration; Computational complexity; Data structures; Equations; Filter bank; Image resolution; Markov random fields; Multiresolution analysis; Signal resolution; Video compression; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applied Imagery Pattern Recognition Workshop, AIPR 2001 30th
Conference_Location :
Washington, DC
Print_ISBN :
0-7695-1245-3
Type :
conf
DOI :
10.1109/AIPR.2001.991214
Filename :
991214
Link To Document :
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