Learning optimization of morphological filters with gray scale structuring elements

Akira Asano; Tohru Yamashita; Shunsuke Yokozeki

doi:10.1117/1.600827

1 August 1996 Learning optimization of morphological filters with gray scale structuring elements

Akira Asano, Tohru Yamashita, Shunsuke Yokozeki

Optical Engineering, Vol. 35, Issue 8, (August 1996). https://doi.org/10.1117/1.600827

Mathematical morphology with gray scale 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 for the combination is still uncertain. In this paper, an optimization method for a mathematical morphological filter with gray scale structuring elements is proposed. This method is based on the concept of a neural network with morphological operations and on learning using simulated annealing. The method is also applied to gray scale bipolar morphological filters for image differentiation.

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Akira Asano, Tohru Yamashita, and Shunsuke Yokozeki "Learning optimization of morphological filters with gray scale structuring elements," Optical Engineering 35(8), (1 August 1996). https://doi.org/10.1117/1.600827

Published: 1 August 1996

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