Self-dual morphological operators and filters
Journal of Mathematical Imaging and Vision
From connected operators to levelings
ISMM '98 Proceedings of the fourth international symposium on Mathematical morphology and its applications to image and signal processing
ISMM '98 Proceedings of the fourth international symposium on Mathematical morphology and its applications to image and signal processing
Connected morphological operators for binary images
Computer Vision and Image Understanding
Mathematical morphology on complete semilattices and its applications to image processing
Fundamenta Informaticae - Special issue on mathematical morphology
Connections for sets and functions
Fundamenta Informaticae - Special issue on mathematical morphology
Inf-Semilattice Approach to Self-Dual Morphology
Journal of Mathematical Imaging and Vision
Journal of Mathematical Imaging and Vision
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
Journal of Mathematical Imaging and Vision
Fast computation of a contrast-invariant image representation
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
A general framework for tree-based morphology and its applications to self-dual filtering
Image and Vision Computing
Permutation-based finite implicative fuzzy associative memories
Information Sciences: an International Journal
Image decompositions and transformations as peaks and wells
ISMM'11 Proceedings of the 10th international conference on Mathematical morphology and its applications to image and signal processing
Self-dual attribute profiles for the analysis of remote sensing images
ISMM'11 Proceedings of the 10th international conference on Mathematical morphology and its applications to image and signal processing
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This paper further investigates a new approach for self-dual morphological processing, where eroded images have all shapes shrunk in a contrast-invariant way. In the binary case, we operate on a given image with morphological operators in the so-called ''adjacency lattice,'' which is intimately related to the image's adjacency tree. These operators are generalized to grayscale images by means of the so-called ''shape-tree semilattice,'' which is based on the tree of shapes of the given image. Apart of reviewing their original definition, different algorithms for computing the shape-tree morphological operators are addressed.