Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Median filter based on fuzzy rules and its application to image restoration
Fuzzy Sets and Systems - Special issue on fuzzy signal processing
Digital image processing
Weighted fuzzy mean filters for image processing
Fuzzy Sets and Systems
Information Sciences—Informatics and Computer Science: An International Journal
High-stability AWFM filter for signal restoration and its hardware design
Fuzzy Sets and Systems
Fuzzy selection filters for image restoration with neural learning
IEEE Transactions on Signal Processing
A new fuzzy logic filter for image enhancement
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Fuzzy stack filters-their definitions, fundamental properties, and application in image processing
IEEE Transactions on Image Processing
Adaptive fuzzy multilevel median filter
IEEE Transactions on Image Processing
A self-organizing feature map-driven approach to fuzzy approximate reasoning
Expert Systems with Applications: An International Journal
An improvement on genetic-based learning method for fuzzy artificial neural networks
Applied Soft Computing
An intelligent image agent based on soft-computing techniques for color image processing
Expert Systems with Applications: An International Journal
Polylinear form of functions on HOSVD basis in relation to Fourier image processing
MATH'09 Proceedings of the 14th WSEAS International Conference on Applied mathematics
The learning algorithm for a novel fuzzy neural network
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
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A multilayer feedforward fuzzy neural network(FNN), by which the predetermined fuzzy system can be realized is constructed to express a given two-dimensional (2-D) digital image. It is shown that such a network is universal approximator. The FNN approach provides us with the representation model of the 2-D discrete image. In noise environment some given fuzzy numbers are employed to describe gray levels of a digital image and the deviation of corrupted image to its noise-free one. A class of fuzzy rules for removing impulse noise in degraded image are presented. The corresponding FNN may work as a filter, which improves the performances of median and rank-conditioned rank selection filters. Especially, such a filter may to a greatest extent maintain the fine structure of the image. Under the minimum mean absolute error criterion the membership functions of fuzzy numbers are adaptively adjusted, and an optimal FNN for image representation is derived in noise environment. Simultaneously some real image examples are systemically analyzed to show that the FNN may result in higher quality global restoration.