LocalStatisticExtraction¶
Computes local statistical moments on every pixel in the selected channel of the input image
Description¶
This application computes the 4 local statistical moments on every pixel in the selected channel of the input image, over a specified neighborhood. The output image is multi band with one statistical moment (feature) per band. Thus, the 4 output features are the Mean, the Variance, the Skewness and the Kurtosis. They are provided in this exact order in the output image.
Parameters¶
Input Image -in image Mandatory
The input image to compute the features on.
Feature Output Image -out image [dtype] Mandatory
Output image containing the local statistical moments.
Selected Channel -channel int Default value: 1
The selected channel index (1 based)
Neighborhood radius -radius int Default value: 3
The computational window radius.
Available RAM (MB) -ram int Default value: 256
Available memory for processing (in MB).
Examples¶
From the command-line:
otbcli_LocalStatisticExtraction -in qb_RoadExtract.tif -channel 1 -radius 3 -out Statistics.tif
From Python:
import otbApplication
app = otbApplication.Registry.CreateApplication("LocalStatisticExtraction")
app.SetParameterString("in", "qb_RoadExtract.tif")
app.SetParameterInt("channel", 1)
app.SetParameterInt("radius", 3)
app.SetParameterString("out", "Statistics.tif")
app.ExecuteAndWriteOutput()