ee_extra.QA.metrics.MSE#

class ee_extra.QA.metrics.MSE(original: Image, modified: Image, reproject: bool = True, **kwargs: Any)[source]#

Calculate band-wise Mean Squared Error (MSE) between an original and modified image with the same bands. A value of 0 represents no error.

Parameters:

  • original – The original image to use as a reference.

  • modified – The modified image to compare to the original.

  • reproject – If true, the original image will be reprojected to the modified image scale before calculation.

  • kwargs – Additional keyword arguments passed to ee.Image.reduceRegion.

Returns:

A dictionary with band names as keys and MSE values as values.

Examples

>>> from ee_extra.QA import metrics
>>> bands = ["B4", "B3", "B2"]
>>> img1 = ee.Image("COPERNICUS/S2_SR/20210703T170849_20210703T171938_T14SPG").select(bands)
>>> img2 = ee.Image("COPERNICUS/S2_SR/20210708T170851_20210708T171925_T14SPG").select(bands)
>>> metrics.MSE(img1, img2, bestEffort=True).getInfo()
{'B2': 1329906.30450367, 'B3': 1175020.2097754816, 'B4': 1199736.6394475223}
__init__()#

Methods

__init__()