def average(image_stack):
sum_image = plimage.create(image_stack[0].xsize, image_stack[0].ysize,
1, gdal.GDT_Float32)
for image in image_stack:
sum_image.bands[0] += image.bands[0]
sum_image.bands[0] = sum_image.bands[0] / len(image_stack)
return sum_image
def snr(image_stack):
image_average = average(image_stack)
image_variance = variance(image_stack)
snr_image = plimage.create(image_stack[0].xsize, image_stack[0].ysize,
1, gdal.GDT_Float32)
# avoid divide by zero
image_variance.bands[0] = numpy.maximum(0.01,image_variance.bands[0])
snr_image.bands[0] = image_average.bands[0]/(image_variance.bands[0] ** 0.5)
return snr_image
def variance(image_stack):
sum_image = plimage.create(image_stack[0].xsize, image_stack[0].ysize,
1, gdal.GDT_Float32)
for img_i in image_stack:
for img_j in image_stack:
img_diff = (img_i.bands[0].astype(numpy.float32) - img_j.bands[0])
sum_image.bands[0] += (img_diff * img_diff) / 2.0
sum_image.bands[0] = sum_image.bands[0] / (len(image_stack) ** 2)
return sum_image
