jlengrand/landsat-util
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skip color correction for ndvi

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Scisco
2016-02-18 14:49:25 -05:00
parent 4b59512742
commit 3d550aef8f
1 changed files with 12 additions and 8 deletions
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20
landsat/image.py
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@@ -269,14 +269,18 @@ class BaseProcess(VerbosityMixin):
return output_file
def _color_correction(self, band, band_id, low, coverage):
self.output("Color correcting band %s" % band_id, normal=True, color='green', indent=1)
p_low, cloud_cut_low = self._percent_cut(band, low, 100 - (coverage * 3 / 4))
temp = numpy.zeros(numpy.shape(band), dtype=numpy.uint16)
cloud_divide = 65000 - coverage * 100
mask = numpy.logical_and(band < cloud_cut_low, band > 0)
temp[mask] = rescale_intensity(band[mask], in_range=(p_low, cloud_cut_low), out_range=(256, cloud_divide))
temp[band >= cloud_cut_low] = rescale_intensity(band[band >= cloud_cut_low], out_range=(cloud_divide, 65535))
return temp
if self.bands == [4, 5]:
return band
else:
self.output("Color correcting band %s" % band_id, normal=True, color='green', indent=1)
p_low, cloud_cut_low = self._percent_cut(band, low, 100 - (coverage * 3 / 4))
temp = numpy.zeros(numpy.shape(band), dtype=numpy.uint16)
cloud_divide = 65000 - coverage * 100
mask = numpy.logical_and(band < cloud_cut_low, band > 0)
temp[mask] = rescale_intensity(band[mask], in_range=(p_low, cloud_cut_low), out_range=(256, cloud_divide))
temp[band >= cloud_cut_low] = rescale_intensity(band[band >= cloud_cut_low],
out_range=(cloud_divide, 65535))
return temp
def _percent_cut(self, color, low, high):
return numpy.percentile(color[numpy.logical_and(color > 0, color < 65535)], (low, high))