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    Angiograph image restoration with the use of rule base fuzzy 2D Kalman filter
    (Pergamon-Elsevier Science Ltd, 2008) Toprak, Abdullah; Gueler, Inan
    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. (C) 2007 Elsevier Ltd. All rights reserved.
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    Öğe
    Impulse noise reduction in medical images with the use of switch mode fuzzy adaptive median filter
    (Academic Press Inc Elsevier Science, 2007) Toprak, Abdullah; Gueler, Inan
    In this paper, a novel fuzzy adaptive median filter is presented for the noise reduction in MR images corrupted with heavy impulse (salt&pepper) noise. We propose a switch mode fuzzy adaptive median filter (SMFAMF) for removing highly corrupted salt&pepper noise without destroying edges and details in the image. The SMFAMF filter is an improved version of adaptive median filter (AMF) in order to reduce additive impulse noise in the images. The proposed filter can preserve details in the images better than AMF while suppressing additive salt&pepper or impulse type noises. In this paper, we placed our preference on bell-shaped membership function with adaptive parameters instead of triangular membership function without variable coefficients in order to observe better results. Experiments with the magnetic resonance (MR) image from healthy subject, an MR image having the opaque material, and an MR image having disease demonstrate the mean square error (MSE), root mean square error (RMSE), signal-to-noise ratio (SNR), and peak signal-to-noise ratio (PSNR) of the proposed method. The results show that the proposed method can be useful for MR images with impulse type noises. (c) 2006 Elsevier Inc. All rights reserved.