Design of soft morphological filters by learning

Pertti T. Koivisto; Pauli Kuosmanen

doi:10.1117/12.172580

1 May 1994 Design of soft morphological filters by learning

Pertti T. Koivisto, Pauli Kuosmanen

Proceedings Volume 2180, Nonlinear Image Processing V; (1994) https://doi.org/10.1117/12.172580
Event: IS&T/SPIE 1994 International Symposium on Electronic Imaging: Science and Technology, 1994, San Jose, CA, United States

Abstract

The choice and detailed design of the structuring elements play a pivotal role in soft morphological processing of images. This paper proposes a learning method for the optimization of the structuring elements of soft morphological filters under given optimization criterium. The learning method is based on simulated annealing. Experimental results depicted herein illustrate that the proposed method can be applied to finding optimal structuring systems in practical situations.

Citation Download Citation

Pertti T. Koivisto and Pauli Kuosmanen "Design of soft morphological filters by learning", Proc. SPIE 2180, Nonlinear Image Processing V, (1 May 1994); https://doi.org/10.1117/12.172580

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