SFSTextureExtraction

Computes Structural Feature Set textures on every pixel of the input image selected channel

Description

Structural Feature Set [1] are based on the histograms of the pixels in multiple directions of the image. The SFSTextureExtraction application computes the 6 following features: SFS’Length, SFS’Width, SFS’PSI, SFS’W-Mean, SFS’Ratio and SFS’SD (Standard Deviation). The texture indices are computed from the neighborhood of each pixel. It is possible to change the length of the calculation line (spatial threshold), as well as the maximum difference between a pixel of the line and the pixel at the center of the neighborhood (spectral threshold) [2].

Parameters

Input Image -in image Mandatory
The input image to compute the features on.

Selected Channel -channel int Default value: 1
The selected channel index

Texture feature parameters

This group of parameters allows one to define SFS texture parameters. The available texture features are SFS’Length, SFS’Width, SFS’PSI, SFS’W-Mean, SFS’Ratio and SFS’SD. They are provided in this exact order in the output image.

Spectral Threshold -parameters.spethre float Default value: 50
Spectral Threshold

Spatial Threshold -parameters.spathre int Default value: 100
Spatial Threshold

Number of Direction -parameters.nbdir int Default value: 20
Number of Direction

Alpha -parameters.alpha float Default value: 1
Alpha

Ratio Maximum Consideration Number -parameters.maxcons int Default value: 5
Ratio Maximum Consideration Number


Feature Output Image -out image [dtype] Mandatory
Output image containing the SFS texture features.

Available RAM (MB) -ram int Default value: 256
Available memory for processing (in MB).

Examples

From the command-line:

otbcli_SFSTextureExtraction -in qb_RoadExtract.tif -channel 1 -parameters.spethre 50.0 -parameters.spathre 100 -out SFSTextures.tif

From Python:

import otbApplication

app = otbApplication.Registry.CreateApplication("SFSTextureExtraction")

app.SetParameterString("in", "qb_RoadExtract.tif")
app.SetParameterInt("channel", 1)
app.SetParameterFloat("parameters.spethre", 50.0)
app.SetParameterInt("parameters.spathre", 100)
app.SetParameterString("out", "SFSTextures.tif")

app.ExecuteAndWriteOutput()

See also

[1] HUANG, Xin, ZHANG, Liangpei, et LI, Pingxiang. Classification and extraction of spatial features in urban areas using high-resolution multispectral imagery. IEEE Geoscience and Remote Sensing Letters, 2007, vol. 4, no 2, p. 260-264.
[2] otbSFSTexturesImageFilter class