Titlebook: Mathematical Morphology and Its Applications to Image and Signal Processing; Petros Maragos,Ronald W. Schafer,Muhammad Akmal Bu Book 1996

neutrophils

担忧

ingestion

Spatially-Variant Mathematical Morphologys. The practical utility of these results requires the representation of nonlinear operators based on a minimal collection of elements of the kernel—minimal basis—in terms of rudimentary morphological operations. A kernel representation of increasing—not necessarily spatially—invariant—operators in

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Discrete Random Functions: Modeling and Analysis Using Mathematical Morphologyasic characterizing functionals of the theory, their properties and interrelationships are proved and it is shown that these functional are sufficient for the complete probabilistic specification of DRF. Morphological tools for modeling and analyzing images are also considered. The major contributio

Solace

谷物

Harass

失望昨天

Region Adjacency Graphs and Connected Morphological Operatorsch operators can be obtained byrepresenting an image as a region adjacency graph, a graph whose vertices represent the componentsof the level sets and whose edges describe adjacency. In this graph connected operators can onlychange grey-values of the vertices. To obtain the adjacency graph of the tr

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Space Connectivity and Translation-Invariancesuch as, for example, to guarantee that a translated connected component is actually a connected component. This is a major issue when connected operators are employed. This work proposes a condition that should be satisfied by the opening γ.in order to avoid the appearance of counter-intuition resu

licence

Alternating Sequential Filters by Adaptive-Neighborhood Structuring Functionsgm of Adaptive-Neighborhood Image Processing, leading to what we have called the Adaptive-Neighborhood Alternating Sequential Filters (ANASFs). By using synthetic and real images to which Gaussian noise was added, we demonstrate the better performance of the open-close and close-open ANASFs against