DocumentCode :
815987
Title :
Separability of spatiotemporal spectra of image sequences
Author :
Eckert, Michael P. ; Buchsbaum, Gershon ; Watson, Andrew B.
Author_Institution :
Dept. of Bioeng., Pennsylvania Univ., Philadelphia, PA, USA
Volume :
14
Issue :
12
fYear :
1992
fDate :
12/1/1992 12:00:00 AM
Firstpage :
1210
Lastpage :
1213
Abstract :
The authors calculate the spatiotemporal power spectrum of 14 image sequences in order to determine the degree to which the spectra are separable in space and time and to assess the validity of the commonly used exponential correlation model. They expand the spectrum by a singular value decomposition into a sum of separable terms and define an index of spatiotemporal separability. as the fraction of the signal energy that can be represented by the first (largest) separable term. All spectra were found to be highly separable with an index of separability above 0.98. The power spectra of the sequences were well fit by a separable model, which corresponds to a product of exponential autocorrelation functions separable in space and time
Keywords :
image sequences; spectral analysis; exponential correlation model; image sequences; singular value decomposition; spatiotemporal power spectrum; spatiotemporal separability; Autocorrelation; Biological system modeling; Cameras; Frequency conversion; Image coding; Image sequences; Layout; Pixel; Spatiotemporal phenomena; Statistics;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.177387
Filename :
177387
Link To Document :
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