Title :
Restoration of images with nonstationary mean and autocorrelation
Author :
Hillery, Allen D. ; Chin, Roland T.
Author_Institution :
Dept. of Electr. Comput. Eng., Wisconsin Univ., Madison, WI, USA
Abstract :
Methods are investigated for the restoration of images degraded by both blur and noise. The objective is to develop estimation strategies to deal with images that exhibit spatially varying statistics. The restoration starts with transforming the image with nonstationary statistics into an image that exhibits stationary characteristics. This transformation can be viewed as a prewhitening filter that normalizes the local mean and local variance of the image, creating a stationary, or near stationary, field. Then the ideal image is estimated from the transformed image on the basis of the linear minimum-mean-square-error criterion. The process removes image blur and noise and at the same time inverts the effects of the transformation
Keywords :
correlation methods; errors; estimation theory; filtering and prediction theory; noise; picture processing; autocorrelation; degraded image; estimation strategies; ideal image; image blur; image noise; image restoration; linear minimum-mean-square-error criterion; local mean; local variance; nonstationary mean; nonstationary statistics; prewhitening filter; spatially varying statistics; stationary characteristics; transformed image; Additive white noise; Autocorrelation; Covariance matrix; Degradation; Filters; Image restoration; Mean square error methods; Statistics; Vectors; White noise;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on
Conference_Location :
New York, NY
DOI :
10.1109/ICASSP.1988.196763
