Gaussian noise reduction in greyscale images
International Journal of Intelligent Systems Technologies and Applications
Computer graphics and image processing tools for visual servoing
ISCGAV'06 Proceedings of the 6th WSEAS International Conference on Signal Processing, Computational Geometry & Artificial Vision
A visual servoing robot control architecture
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
Do fuzzy techniques offer an added value for noise reduction in images?
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
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We propose a fuzzy rule-based approach to image enhancement to address its seemingly conflicting goals: (a) removing impulse noise, (b) smoothing out nonimpulse noise, and (c) enhancing edges or certain other salient features. Three different filters for each task are derived using the weighted least mean squared method. Criteria for selecting each filter are defined. The criteria are based on the local context as well as the particular situation. They constitute the antecedent clauses of the fuzzy rules, and the corresponding filters constitute the consequent clauses of the fuzzy rules. The overall result of the fuzzy rule-based system is computed as the combination of the results of the individual filters, where each result contributes to the degree that the corresponding antecedent clause is satisfied. This approach gives us a powerful and flexible image enhancement paradigm. Experimental results are presented.