Optimal composite morphological supervised filter for image denoising using genetic programming: Application to magnetic resonance images

Composite filters based on mathematical morphological operators (MMO) are getting considerable attraction in image denoising. Most of such approaches depend on pre-fixed combination of MMO. In this paper, we proposed a genetic programming (GP) based approach for denoising magnetic resonance images (...

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Bibliographic Details
Published in:	Engineering applications of artificial intelligence Vol. 31; pp. 78 - 89
Main Authors:	Sharif, Muhammad, Arfan Jaffar, Muhammad, Tariq Mahmood, Muhammad
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.05.2014
Subjects:	Genetic programming Genetics Image restoration Magnetic resonance Magnetic resonance imaging Mathematical morphology Modules Noise reduction Optimization Preprocessing Programming Rician noise Image restoration Magnetic resonance imaging Rician noise Mathematical morphology Genetic programming
ISSN:	0952-1976, 1873-6769
Online Access:	Get full text
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