MorphologicalClassification - Morphological Classification

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

Detailed 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 f denote the input image and \psi_{N}(f) the geodesic leveling of f with a structuring element of size N. One can derive the following decision rule to classify f into Convex (label \stackrel{\smile}{k}), Concave (label \stackrel{\frown}{k}) and Flat (label \bar{k}):

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}

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

Parameters

This section describes in details the parameters available for this application. Table [1] presents a summary of these parameters and the parameters keys to be used in command-line and programming languages. Application key is MorphologicalClassification .

[1]Table: Parameters table for Morphological Classification.
Parameter Key Parameter Name Parameter Type
in Input Image Input image
out Output Image Output image
channel Selected Channel Int
ram Available RAM (Mb) Int
structype Structuring Element Type Choices
structype ball Choice Ball
structype cross Choice Cross
radius Radius Int
sigma Sigma value for leveling tolerance Float
inxml Load otb application from xml file XML input parameters file
outxml Save otb application to xml file XML output parameters file
  • Input Image: The input image to be classified.
  • Output Image: The output classified image with 3 different values (0 : Flat, 1 : Convex, 2 : Concave).
  • Selected Channel: The selected channel index for input image.
  • Available RAM (Mb): Available memory for processing (in MB).
  • Structuring Element Type: Choice of the structuring element type. Available choices are:
  • Ball
  • Cross
  • Radius: Radius of the structuring element (in pixels).
  • Sigma value for leveling tolerance: Sigma value for leveling tolerance.
  • Load otb application from xml file: Load otb application from xml file.
  • Save otb application to xml file: Save otb application to xml file.

Example

To run this example in command-line, use the following:

otbcli_MorphologicalClassification -in ROI_IKO_PAN_LesHalles.tif -channel 1 -structype ball -radius 5 -sigma 0.5 -out output.tif

To run this example from Python, use the following code snippet:

#!/usr/bin/python

# Import the otb applications package
import otbApplication

# The following line creates an instance of the MorphologicalClassification application
MorphologicalClassification = otbApplication.Registry.CreateApplication("MorphologicalClassification")

# The following lines set all the application parameters:
MorphologicalClassification.SetParameterString("in", "ROI_IKO_PAN_LesHalles.tif")

MorphologicalClassification.SetParameterInt("channel", 1)

MorphologicalClassification.SetParameterString("structype","ball")

MorphologicalClassification.SetParameterInt("radius", 5)

MorphologicalClassification.SetParameterFloat("sigma", 0.5)

MorphologicalClassification.SetParameterString("out", "output.tif")

# The following line execute the application
MorphologicalClassification.ExecuteAndWriteOutput()

Limitations

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

Authors

This application has been written by OTB-Team.

See Also

These additional resources can be useful for further information:

otbConvexOrConcaveClassificationFilter class