Suppression of Interference Caused by Fragment Brownian Movement Through the Utilisation of Fuzzy Formulation (Journal of Nonlinear Modeling and Analysis, 2024)
The proposed fuzzy composition-based filtering method aims toremove a presence of fractal Brownian noise in the MR brain images. Thefractional Brownian motion (FBM) noise is a continuous time Gaussian processed noise and its very difficult to identify the positions and range of noisedensity level, due to a smoothed noise. The projected fuzzy scheme enclosesan equivalent fuzzy interference scheme, a fuzzy average procedure and a fuzzycomposition procedure. The noise subtraction scheme has been confirmed tobe the finest while the depiction is tainted by means of fractional Brownianmotion. With an average o/p Peak Signal to Noise Ratio (PSNR) of 37.22 andan average noisy image PSNR of 20.28, the average PSNR rate has improvedby 16.94. In addition, the average mean square error (MSE) rate has decreasedfrom 609.48 to 12.33 percent. An experimental result confirms that the fuzzyfiltering achieves an outstanding eminence of reinstated images in terms ofPSNR and MSE without the assistance of noiseless depiction.
Keywords: FBM; parallel FIS; FM process; FC process; MRI brain; PSNR; MSE.