ee.Kernel.roberts
Generates a 2x2 Roberts edge-detection kernel.
Usage | Returns |
---|
ee.Kernel.roberts(magnitude, normalize) | Kernel |
Argument | Type | Details |
---|
magnitude | Float, default: 1 | Scale each value by this amount. |
normalize | Boolean, default: false | Normalize the kernel values to sum to 1. |
Examples
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
from pprint import pprint
print('A Roberts kernel:')
pprint(ee.Kernel.roberts().getInfo())
# 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.
[null,null,["Last updated 2023-10-06 UTC."],[[["Creates a 2x2 kernel used for Roberts edge detection, a method for identifying edges in images by approximating the gradient."],["The kernel's values can be scaled using the `magnitude` parameter and normalized to sum to 1 using the `normalize` parameter."],["The default kernel has the values `[[1, 0], [0, -1]]`, which represent the weights applied to neighboring pixels to calculate the edge strength."]]],[]]