DocumentCode :
3382170
Title :
Least-squares reconstruction of an image from its noisy observations using the bispectrum
Author :
Erdem, A. Tanju ; Sezan, M. Ibrahim
Author_Institution :
Imaging Res. Labs., Eastman Kodak Co., Rochester, NY, USA
fYear :
1992
fDate :
7-9 Oct 1992
Firstpage :
156
Lastpage :
159
Abstract :
The observed images are allowed to be spatially shifted with respect to one another, and the observation noise is assumed to be Gaussian. An algorithm is proposed that recovers the image by separately reconstructing its Fourier phase and Fourier log-magnitude, in the least-squares sense, from the modulo-2π phase and log-magnitude of the bispectrum of the image estimated from the given noisy observations. A technique proposed by the authors is used to unwrap the modulo-2π bispectral phase and to reconstruct the Fourier phase of the image. Experimental results demonstrate the performance of the proposed algorithm
Keywords :
image reconstruction; image sequences; least squares approximations; random noise; spectral analysis; Fourier log-magnitude; Fourier phase; Gaussian noise; bispectrum; least-squares image reconstruction; noisy observations; performance; proposed algorithm; Discrete Fourier transforms; Filtering; Gaussian noise; Image reconstruction; Image sequences; Laboratories; Noise measurement; Phase measurement; Phase noise; White noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Statistical Signal and Array Processing, 1992. Conference Proceedings., IEEE Sixth SP Workshop on
Conference_Location :
Victoria, BC
Print_ISBN :
0-7803-0508-6
Type :
conf
DOI :
10.1109/SSAP.1992.246825
Filename :
246825
Link To Document :
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