The mathematical morphology with grayscale structuring elements has attracted much attention since combinations of the operations in this class can realize almost all noise removing filters. However, the optimization method of the combination is still uncertain. In this paper, an optimization method of the mathematical morphological filter with grayscale structuring elements is proposed. This method is based on the concept of the neural network with morphological operations and the learning using the simulated annealing. The method is also applied for the grayscale bipolar morphological filters for the image differentiation.
Mathematical morphology, Nonlinear filter, Image processing, Simulated annealing, Neural networks.