eemont.image.panSharpen
- eemont.image.panSharpen(self, method='SFIM', qa=None, **kwargs)[source]
Apply panchromatic sharpening to the Image.
Optionally, run quality assessments between the original and sharpened Image to measure spectral distortion and set results as properties of the sharpened Image.
- Parameters
self (ee.Image [this]) – Image to sharpen.
method (str, default="SFIM") – The sharpening algorithm to apply. Current options are “SFIM” (Smoothing Filter-based Intensity Modulation), “HPFA” (High Pass Filter Addition), “PCS” (Principal Component Substitution), and “SM” (simple mean). Different sharpening methods will produce different quality sharpening results in different scenarios.
qa (str | list, default=None) – One or more optional quality assessment names to apply after sharpening. Results will be stored as image properties with the pattern eemont:metric, e.g. eemont:RMSE.
**kwargs – Keyword arguments passed to ee.Image.reduceRegion() such as “geometry”, “maxPixels”, “bestEffort”, etc. These arguments are only used for PCS sharpening and quality assessments.
- Returns
The Image with all sharpenable bands sharpened to the panchromatic resolution and quality assessments run and set as properties.
- Return type
ee.Image
Examples
>>> import ee, eemont >>> ee.Authenticate() >>> ee.Initialize() >>> source = ee.Image("LANDSAT/LC08/C01/T1_TOA/LC08_047027_20160819") >>> sharp = source.panSharpen(method="HPFA", qa=["MSE", "RMSE"], maxPixels=1e13)