ee.Kernel.laplacian8
Generates a 3x3 Laplacian-8 edge-detection kernel.
| Usage | Returns |
|---|
ee.Kernel.laplacian8(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 Laplacian-8 kernel', ee.Kernel.laplacian8());
/**
* Output weights matrix
*
* [1, 1, 1]
* [1, -8, 1]
* [1, 1, 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 Laplacian-8 kernel:')
pprint(ee.Kernel.laplacian8().getInfo())
# Output weights matrix
# [1, 1, 1]
# [1, -8, 1]
# [1, 1, 1]
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Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[[["Creates a 3x3 kernel for edge detection using the Laplacian-8 algorithm."],["The kernel has a center weight of -8 and surrounding weights of 1, enhancing edges in an image."],["Users can adjust the `magnitude` to scale the kernel values and `normalize` them to sum to 1."]]],["The `ee.Kernel.laplacian8()` function generates a 3x3 Laplacian-8 edge-detection kernel. It accepts two optional arguments: `magnitude` (float, default 1) to scale kernel values, and `normalize` (boolean, default false) to normalize values to sum to 1. The function returns a Kernel object. The default kernel matrix consists of ones around the perimeter and negative eight in the center: [[1, 1, 1], [1, -8, 1], [1, 1, 1]].\n"]]