Abstract
This paper is focused on adaptive viscous morphology in the context of the General Adaptive Neighborhood Image Processing (GANIP) approach [1,2]. A local adaptive neighborhood is defined for each image point, depending on the intensity function of the image. These so-called General Adaptive Neighborhoods (GANs) are used as adaptive structuring elements for Mathematical Morphology (MM) [1,3]. In this paper, GAN-based viscous MM is introduced to adjust the filtering activity to the image gray levels. The proposed GAN viscous morphological filters are successfully applied on real application examples in image restoration and enhancement.
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Debayle, J., Pinoli, JC. (2011). General Adaptive Neighborhood Viscous Mathematical Morphology. In: Soille, P., Pesaresi, M., Ouzounis, G.K. (eds) Mathematical Morphology and Its Applications to Image and Signal Processing. ISMM 2011. Lecture Notes in Computer Science, vol 6671. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21569-8_20
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DOI: https://doi.org/10.1007/978-3-642-21569-8_20
Publisher Name: Springer, Berlin, Heidelberg
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