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An enhanced median filter for removing noise from MR images

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Version 2 2024-06-18, 10:59
Version 1 2018-10-26, 14:36
journal contribution
posted on 2024-06-18, 10:59 authored by S Arastehfar, Ali A Pouyan, Athena Jalalian
In this paper, a novel decision based median (DBM) filter for enhancing MR images has been proposed. The method is based on eliminating impulse noise from MR images. A median-based method to remove impulse noise from digital MR images has been developed. Each pixel is leveled from black to white like gray-level. The method is adjusted in order to decide whether the median operation can be applied on a pixel. The main deficiency in conventional median filter approaches is that all pixels are filtered with no concern about healthy pixels. In this research, to suppress this deficiency, noisy pixels are initially detected, and then the filtering operation is applied on them. The proposed decision method (DM) is simple and leads to fast filtering. The results are more accurate than other conventional filters. Moreover, DM adjusts itself based on the conditions of local detections. In other words, DM operation on detecting a pixel as a noise depends on the previous decision. As a considerable advantage, some unnecessary median operations are eliminated and the number of median operations reduces drastically by using DM. Decision method leads to more acceptable results in scenarios with high noise density. Furthermore, the proposed method reduces the probability of detecting noise-free pixels as noisy pixels and vice versa.

History

Journal

Journal of Artificial Intelligence & Data Mining

Volume

1

Season

Winter and Spring

Article number

6

Pagination

13-17

Location

Shahrood, Iran

Open access

  • Yes

ISSN

2322-5211

eISSN

2322-4444

Language

eng

Publication classification

X Not reportable, CN.1 Other journal article

Copyright notice

2013, S Arastehfar, Ali A Pouyan, A Jalalian

Issue

1

Publisher

Shahrood University of Technology

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