Morphological Classification

Brief Description

Performs morphological convex, concave and flat classification on an input image channel

Tags

Feature Extraction, Morphology

Long Description

This algorithm is based on the following publication:
Martino Pesaresi and Jon Alti Benediktsson, Member, IEEE: A new approach for the morphological segmentation of high resolution satellite imagery.
IEEE Transactions on geoscience and remote sensing, vol. 39, NO. 2, February 2001, p. 309-320.

This application perform the following decision rule to classify a pixel between the three classes Convex, Concave and Flat. Let :math:`f` denote the input image and :math:`\psi_{N}(f)` the geodesic leveling of :math:`f` with a structuring element of size :math:`N`. One can derive the following decision rule to classify :math:`f` into Convex (label :math:`\stackrel{\smile}{k}`), Concave (label :math:`\stackrel{\frown}{k}`) and Flat (label :math:`\bar{k}`):
:math:`f(n) = \begin{cases} \stackrel{\smile}{k} & : f-\psi_{N}(f)>\sigma \\ \stackrel{\frown}{k} & : \psi_{N}(f)-f>\sigma \\ \bar{k} & : \mid f - \psi_{N}(f) \mid \leq \sigma \end{cases}`

The output is a labeled image (0 : Flat, 1 : Convex, 2 : Concave)

Parameters

Limitations

Generation of the morphological classification is not streamable, pay attention to this fact when setting the radius size of the structuring element.

Authors

OTB-Team

See also

otbConvexOrConcaveClassificationFilter class

Example of use