@Article{JNMA-6-228,
author = {Kathikeyan , V.Balamurugan , K.Visu , Y.Palin and Prakash , R.Varun},
title = {Suppression of Interference Caused by Fragment Brownian Movement Through the Utilisation of Fuzzy Formulation},
journal = {Journal of Nonlinear Modeling and Analysis},
year = {2024},
volume = {6},
number = {2},
pages = {228--237},
abstract = {<p style="text-align: justify;">The proposed fuzzy composition-based filtering method aims to
remove a presence of fractal Brownian noise in the MR brain images. The
fractional Brownian motion (FBM) noise is a continuous time Gaussian processed noise and its very difficult to identify the positions and range of noise
density level, due to a smoothed noise. The projected fuzzy scheme encloses
an equivalent fuzzy interference scheme, a fuzzy average procedure and a fuzzy
composition procedure. The noise subtraction scheme has been confirmed to
be the finest while the depiction is tainted by means of fractional Brownian
motion. With an average o/p Peak Signal to Noise Ratio (PSNR) of 37.22 and
an average noisy image PSNR of 20.28, the average PSNR rate has improved
by 16.94. In addition, the average mean square error (MSE) rate has decreased
from 609.48 to 12.33 percent. An experimental result confirms that the fuzzy
filtering achieves an outstanding eminence of reinstated images in terms of
PSNR and MSE without the assistance of noiseless depiction.</p>},
issn = {2562-2862},
doi = {https://doi.org/10.12150/jnma.2024.228},
url = {http://global-sci.org/intro/article_detail/jnma/23172.html}
}