Optimal mean-square N-observation digital morphological filters: i. optimal binary filters
CVGIP: Image Understanding
Optimal mean-square N-observation digital morphological filters: ii. optimal gray-scale filters
CVGIP: Image Understanding
Computational mathematical morphology
Signal Processing - Special issue on mathematical morphology and its applications to signal processing
Mean-absolute-error representation and optimization of computational-morphological filters
Graphical Models and Image Processing
Representation of gray-scale windowed operators
ISMM '98 Proceedings of the fourth international symposium on Mathematical morphology and its applications to image and signal processing
Signal Processing
Enhancement and Restoration of Digital Documents: Statistical Design of Nonlinear Algorithms
Enhancement and Restoration of Digital Documents: Statistical Design of Nonlinear Algorithms
Nonlinear Filters for Image Processing
Nonlinear Filters for Image Processing
Multiresolution Design of Aperture Operators
Journal of Mathematical Imaging and Vision
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Aperture filters compose a recently introduced class of non-linear operators used in signal processing. Their operation involves filtering of signals that are observed within a window of finite width and height. They allow a tractable design of non-linear filters by reducing the search space. This paper presents an adaptation to the original design involving multiple masks with shapes chosen to fit commonly occurring patterns of the input signal. The information obtained using the different masks is efficiently combined to produce the multi-mask filter, which is optimal with respect to the class. This paper demonstrates that for smaller training set sizes the multi-mask filter is well trained and therefore performs better than a single aperture filter with the same data.