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ee.Kernel.roberts
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The ee.Kernel.roberts() function generates a 2x2 Roberts edge-detection kernel.
The magnitude argument scales the kernel values, and the normalize argument can normalize them to sum to 1.
The examples show how to use the ee.Kernel.roberts() function in both the Code Editor (JavaScript) and Colab (Python).
Generates a 2x2 Roberts edge-detection kernel.
Usage Returns ee.Kernel.roberts(magnitude , normalize )Kernel
Argument Type Details magnitudeFloat, default: 1 Scale each value by this amount. normalizeBoolean, default: false Normalize the kernel values to sum to 1.
Examples
Code Editor (JavaScript)
print ( 'A Roberts kernel' , ee . Kernel . roberts ());
/**
* Output weights matrix; center is position [1,1]
*
* [1, 0]
* [0, -1]
*/
Python setup
See the
Python Environment page for information on the Python API and using
geemap for interactive development.
import ee
import geemap.core as geemap
Colab (Python)
display ( 'A Roberts kernel:' , ee . Kernel . roberts ())
# Output weights matrix; center is position [1,1]
# [1, 0]
# [0, -1]
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License , and code samples are licensed under the Apache 2.0 License . For details, see the Google Developers Site Policies . Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2023-10-06 UTC.
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