A fuzzy impulse noise detection and reduction method

Removing or reducing impulse noise is a very active research area in image processing. In this paper we describe a new algorithm that is especially developed for reducing all kinds of impulse noise: fuzzy impulse noise detection and reduction method (FIDRM). It can also be applied to images having a...

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Bibliographic Details
Published in:IEEE transactions on image processing 2006-05, Vol.15 (5), p.1153-1162
Main Authors: Schulte, S., Nachtegael, M., De Witte, V., Van der Weken, D., Kerre, E.E.
Format: Article
Language:English
Subjects:
Active noise reduction
Algorithms
Applied sciences
Artificial Intelligence
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Filtering
Filters
Fuzzy
Fuzzy filter
Fuzzy Logic
Fuzzy set theory
Fuzzy sets
Gray-scale
Image edge detection
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image processing
impulse noise
Impulses
Information Storage and Retrieval - methods
Information, signal and communications theory
membership functions
Noise
Noise generators
Noise reduction
Pattern Recognition, Automated - methods
Pixel
Reduction
Signal and communications theory
Signal processing
Signal Processing, Computer-Assisted
Signal, noise
Studies
Telecommunications and information theory
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Summary:Removing or reducing impulse noise is a very active research area in image processing. In this paper we describe a new algorithm that is especially developed for reducing all kinds of impulse noise: fuzzy impulse noise detection and reduction method (FIDRM). It can also be applied to images having a mixture of impulse noise and other types of noise. The result is an image quasi without (or with very little) impulse noise so that other filters can be used afterwards. This nonlinear filtering technique contains two separated steps: an impulse noise detection step and a reduction step that preserves edge sharpness. Based on the concept of fuzzy gradient values, our detection method constructs a fuzzy set impulse noise. This fuzzy set is represented by a membership function that will be used by the filtering method, which is a fuzzy averaging of neighboring pixels. Experimental results show that FIDRM provides a significant improvement on other existing filters. FIDRM is not only very fast, but also very effective for reducing little as well as very high impulse noise.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2005.864179