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 (...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Engineering applications of artificial intelligence Ročník 31; s. 78 - 89
Hlavní autoři:	Sharif, Muhammad, Arfan Jaffar, Muhammad, Tariq Mahmood, Muhammad
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.05.2014
Témata:	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
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!