IEEE Transactions on Image Processing · 1997 · 208 citations · 48 references
ArtsComputer ScienceComputer VisionDigital ImagingLogicDigital Image ProcessingFuzzy LogicImage AnalysisImage EnhancementImage FilteringImage ProcessingDigital Image EnhancementEdge EnhancementFiltersFuzzy Rule-based SystemsImage SharpeningImage SmoothingImpulse NoiseWeighted Least Squares
In this paper, we propose a robust approach to image enhancement based on fuzzy logic that addresses the seemingly conflicting goals of image enhancement: (i) removing impulse noise, (ii) smoothing out nonimpulse noise, and (iii) enhancing (or preserving) edges and certain other salient structures. We derive three different filters for each of the above three tasks using the weighted (or fuzzy) least squares (LS) method, and define the criteria for selecting each of the three filters. The criteria are based on the local context, and they constitute the antecedent clauses of the fuzzy rules. The overall result of the fuzzy rule-based system is 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. Results of the proposed method on several types of images are compared with those of other standard techniques.
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Robust Regression and Outlier Detection
Gregory F. Piepel, Peter J. Rousseeuw, Annick M. Leroy · Technometrics · 1989 · 6.2K citations
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David Ruppert, Frank R. Hampel, Elvezio Ronchetti et al. · Technometrics · 1987 · 3.8K citations