Mathematical morphology (MM) is a theory and technique for the analysis and processing of geometrical structures, based on set theory, lattice theory, topology, and random functions. MM is most commonly applied to digital images, but it can be employed as well on Graph (mathematics)|graphs, polygon mesh|surface meshes, Solid geometry|solids, and many other spatial structures.Topology|Topological and Geometry|geometrical continuum (theory)|continuous-space concepts such as size, shape, convex set|convexity, Connectedness|connectivity, and geodesic distance, were introduced by MM on both continuous and discrete spaces. MM is also the foundation of morphological image processing, which consists of a set of operators that transform images according to the above characterizations.
MM was originally developed for binary images, and was later extended to grayscale Function (mathematics)|functions and images. The subsequent generalization to complete lattices is widely accepted today as MM's theoretical foundation.
Mathematical morphology (MM) is a theory and technique for the analysis and processing of geometrical structures, based on set theory, lattice theory, topology, and random functions. MM is most commonly applied to digital images, but it can be employed as well on Graph (mathematics)|graphs, polygon mesh|surface meshes, Solid geometry|solids, and many other spatial structures.Topology|Topological and Geometry|geometrical continuum (theory)|continuous-space concepts such as size, shape, convex set|convexity, Connectedness|connectivity, and geodesic distance, were introduced by MM on both continuous and discrete spaces. MM is also the foundation of morphological image processing, which consists of a set of operators that transform images according to the above characterizations.
MM was originally developed for binary images, and was later extended to grayscale Function (mathematics)|functions and images. The subsequent generalization to complete lattices is widely accepted today as MM's...