AI-generated Key Takeaways
-
The
ee.Kernel.roberts()function generates a 2x2 Roberts edge-detection kernel. -
The
magnitudeargument scales the kernel values, and thenormalizeargument 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).
| 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
Code Editor (JavaScript)
print('A Roberts kernel', ee.Kernel.roberts()); /** * Output weights matrix; center is position [1,1] * * [1, 0] * [0, -1] */
import ee import geemap.core as geemap
Colab (Python)
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]