Adaptive mathematical morphology: a unified representation theory

Authors:
Nidhal Bouaynaya;Dan Schonfeld
Affiliations:
Department of Systems Engineering, University of Arkansas at Little Rock;Department of Electrical and Computer Engineering, University of Illinois at Chicago
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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Abstract

In this paper, we present a general theory of adaptive mathematical morphology (AMM) in the Euclidean space. The proposed theory preserves the notion of a structuring element, which is crucial in the design of geometrical signal and image processing applications. Moreover, we demonstrate the theoretical and practical distinctions between adaptive and spatially-variant mathematical morphology. We provide examples of the use of AMM in various image processing applications, and show the power of the proposed framework in image denoising and segmentation.