Title :
Robust modeling for image restoration using a modified reduced update Kalman filter
Author :
Belaifa, Hosni B H ; Schwartz, Howard M.
Author_Institution :
Carleton Univ., Ottawa, Ont., Canada
fDate :
10/1/1992 12:00:00 AM
Abstract :
An algorithm to estimate the original image intensity from a degraded image is developed. The degradation phenomena is a Gaussian noise contaminated by an outlier sequence. The proposed algorithm is a combination of the robust algorithm proposed by Kashyap and Eom (1988) and the reduced update Kalman filter (RUKF) developed by Woods and Radewan (1977). The proposed algorithm is compared to some commonly used techniques such as the median filter, the robust algorithm, and the RUKF
Keywords :
Kalman filters; digital filters; image reconstruction; Gaussian noise; image intensity; image restoration; median filter; modified reduced update Kalman filter; outlier sequence; robust algorithm; robust modeling; Degradation; Filters; Gaussian noise; Image restoration; Iterative algorithms; Least squares approximation; Noise robustness; Parameter estimation; Pixel; Signal processing algorithms;
Journal_Title :
Signal Processing, IEEE Transactions on
