Develop of mean filter for Gaussian image noise removal
Author
Source
Journal of Babylon University : Journal of Applied and Pure Sciences
Issue
Vol. 24, Issue 7 (31 Dec. 2016), pp.1963-1969, 7 p.
Publisher
Publication Date
2016-12-31
Country of Publication
Iraq
No. of Pages
7
Main Subjects
Engineering & Technology Sciences (Multidisciplinary)
Abstract EN
Image can be corrupted during capturing, transmission or storing it.
During this processes images are distorted due to different noises.
There are many methods for reducing noise.
Traditional mean filter considered as a linear filter, that simple, native and appropriates to removing an Additive noise such as Gaussian noise.
Unfortunately, the mean filter suffer from inefficiency of reducing the noise.
This paper proposed a new developed mean filter to speed up and enhance the competence of the traditional mean filter.
The new filter use subset of pixels in the mask to find the new value of the pixel.
The quality of the enhanced images is measured by the statistical quantity measures: Peak Signal-to-Noise Ratio (PSNR) and The Structural Similarity (SSIM) metrics.
A time complexities comparison will be explained between developed and traditional filters
American Psychological Association (APA)
Abbud, Ilaf Ali. 2016. Develop of mean filter for Gaussian image noise removal. Journal of Babylon University : Journal of Applied and Pure Sciences،Vol. 24, no. 7, pp.1963-1969.
https://search.emarefa.net/detail/BIM-1315130
Modern Language Association (MLA)
Abbud, Ilaf Ali. Develop of mean filter for Gaussian image noise removal. Journal of Babylon University : Journal of Applied and Pure Sciences Vol. 24, no. 7 (2016), pp.1963-1969.
https://search.emarefa.net/detail/BIM-1315130
American Medical Association (AMA)
Abbud, Ilaf Ali. Develop of mean filter for Gaussian image noise removal. Journal of Babylon University : Journal of Applied and Pure Sciences. 2016. Vol. 24, no. 7, pp.1963-1969.
https://search.emarefa.net/detail/BIM-1315130
Data Type
Journal Articles
Language
English
Notes
Text in English ; abstracts in English and Arabic.
Record ID
BIM-1315130