A hybrid neuro-fuzzy filter for edge preserving restoration of images corrupted by impulse noise

A new operator for restoring digital images corrupted by impulse noise is presented. The proposed operator is a hybrid filter obtained by appropriately combining a median filter, an edge detector, and a neuro-fuzzy network. The internal parameters of the neuro-fuzzy network are adaptively optimized...

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Bibliographic Details
Published in:IEEE transactions on image processing 2006-04, Vol.15 (4), p.928-936
Main Author: Yuksel, M.E.
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Artificial intelligence
Computer science
control theory
systems
Connectionism. Neural networks
Detection, estimation, filtering, equalization, prediction
Detectors
Digital filters
Digital images
Exact sciences and technology
Fuzzy Logic
Fuzzy neural networks
Fuzzy systems
Image edge detection
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image processing
Image restoration
Impulses
Information filtering
Information filters
Information Storage and Retrieval - methods
Information, signal and communications theory
Models, Statistical
Neural networks
Neural Networks (Computer)
neuro-fuzzy systems
Noise
Nonlinear distortion
nonlinear filters
Numerical Analysis, Computer-Assisted
Operators
Pattern recognition
Pattern Recognition, Automated - methods
Restoration
Signal and communications theory
Signal processing
Signal Processing, Computer-Assisted
Signal, noise
Stochastic Processes
Telecommunications and information theory
Texture
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Description
Summary:A new operator for restoring digital images corrupted by impulse noise is presented. The proposed operator is a hybrid filter obtained by appropriately combining a median filter, an edge detector, and a neuro-fuzzy network. The internal parameters of the neuro-fuzzy network are adaptively optimized by training. The training is easily accomplished by using simple artificial images that can be generated in a computer. The most distinctive feature of the proposed operator over most other operators is that it offers excellent line, edge, detail, and texture preservation performance while, at the same time, effectively removing noise from the input image. Extensive simulation experiments show that the proposed operator may be used for efficient restoration of digital images corrupted by impulse noise without distorting the useful information in the image.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2005.863941