ee.Kernel.sobel

  • Generates a 3x3 Sobel kernel for edge detection in images.

  • The kernel can be scaled using the magnitude argument.

  • Optionally, the kernel values can be normalized to sum to 1 using the normalize argument.

  • Usage examples are provided in JavaScript, Python, and Colab environments.

 Generates a 3x3 Sobel edge-detection kernel.

UsageReturns
ee.Kernel.sobel(magnitude, normalize)Kernel
ArgumentTypeDetails
magnitudeFloat, default: 1Scale each value by this amount.
normalizeBoolean, default: falseNormalize the kernel values to sum to 1.

Examples

Code Editor (JavaScript)

print('A Sobel kernel', ee.Kernel.sobel());

/**
 * Output weights matrix
 *
 * [-1, 0, 1]
 * [-2, 0, 2]
 * [-1, 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)

from pprint import pprint

print('A Sobel kernel:')
pprint(ee.Kernel.sobel().getInfo())

#  Output weights matrix

#  [-1, 0, 1]
#  [-2, 0, 2]
#  [-1, 0, 1]