Fuzzy mathematical approach to pattern recognition
Fuzzy mathematical approach to pattern recognition
Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Automatically determine the membership function based on the maximum entropy principle
Information Sciences: an International Journal
A Note on the Quantitative Measure of Image Enhancement Through Fuzziness
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image thresholding using fuzzy entropies
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Image Enhancement Using Multi-objective Genetic Algorithms
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
Information Sciences: an International Journal
The Visual Computer: International Journal of Computer Graphics
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This paper presents an automated fuzziness-driven algorithm for image enhancement. A class of parametric indices of fuzziness is introduced, which serves as the optimization criterion of the contrast-enhancement procedure. We show that the parametric class of indices constitutes a one-parameter generalization of the linear index of fuzziness of a set. The modification of the membership values of image pixels in the fuzzy plane is performed by finding the optimal S-function, which maximizes the parametric index of fuzziness (PIF). The first-order fuzzy moment of the image is used for tuning the PIF. Experimental results demonstrate the efficiency of the proposed framework in enhancing even highly low-contrasted images and also its ability to improve existing contrast-enhancing algorithms.