Angiograph image restoration with the use of rule base fuzzy 2D Kalman filter
Recursive estimation techniques such as Kalman filter have been used for a long time in image restoration. The aim of this paper is restoration of the images, which are heavy corrupted with the mix of Gaussian and impulse noises, by using novel rule base fuzzy 2D Kalman filter (RBFK). Rule base fuzzy 2D Kalman filter has been utilized for restoration of image which is contaminated with random noises. In the first step of the study, the noisy images were converted to stack which includes several stationary images in order to apply Kalman filter. The experiments which are indicated that rule based fuzzy 2D Kalman filter is one of the best techniques to remove the mix of Gaussian and impulse noises. Altough, Kalman Filter is used in motion images, in this study, it was applied to the stationary images which were duplicated many times to obtain stack.
image restoration rule base fuzzy 2d kalman filter kalman filter gaussian and impulse noise