Adaptive Fuzzy Morphological Filtering of Impulse Noisein Images
Multidimensional Systems and Signal Processing
On Endmember Detection in Hyperspectral Images with Morphological Associative Memories
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
An impulsive noise color image filter using learning-based color morphological operations
Digital Signal Processing
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
A Hybrid Intelligent Morphological Approach for Stock Market Forecasting
Neural Processing Letters
Expert Systems with Applications: An International Journal
A shift-invariant morphological system for software development cost estimation
Expert Systems with Applications: An International Journal
Hybrid morphological methodology for software development cost estimation
Expert Systems with Applications: An International Journal
A Morphological-Rank-Linear evolutionary method for stock market prediction
Information Sciences: an International Journal
| Hi-index | 0.02 |
A class of morphological/rank/linear (MRL)-filters is presented as a general nonlinear tool for image processing. They consist of a linear combination between a morphological/rank filter and a linear filter. A gradient steepest descent method is proposed to optimally design these filters, using the averaged least mean squares (LMS) algorithm. The filter design is viewed as a learning process, and convergence issues are theoretically and experimentally investigated. A systematic approach is proposed to overcome the problem of nondifferentiability of the nonlinear filter component and to improve the numerical robustness of the training algorithm, which results in simple training equations. Image processing applications in system identification and image restoration are also presented, illustrating the simplicity of training MRL-filters and their effectiveness for image/signal processing