1 August 1996 Learning optimization of morphological filters with gray scale structuring elements
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Abstract
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.
Akira Asano, Akira Asano, Tohru Yamashita, Tohru Yamashita, Shunsuke Yokozeki, 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 . Submission:
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