#Imports

import os,glob

os.chdir(r'C:\Users\username\GitHubRepository\Micasense\imageprocessing')

import cv2 #openCV

import exiftool

exiftoolPath = None

if os.name == 'nt':

exiftoolPath = 'C:/exiftool/exiftool(-k).exe' ##Check application name of future versions

with exiftool.ExifTool(exiftoolPath) as exift:

print('Exiftool works!')

import numpy as np

import matplotlib.pyplot as plt #%matplotlib inline

import math

from PIL import Image

import micasense.plotutils as plotutils #Micasense utility modules

import micasense.metadata as metadata

import micasense.utils as msutils

##############################################################################

#Part 1

#Set folder paths

CalibrationFolder_preflight = r'C:\Users\username\GitHubRepository\batch-imageprocessing\test_images\images_calibration\preflight'

CalibrationFolder_postflight = r'C:\Users\username\GitHubRepository\batch-imageprocessing\test_images\images_calibration\postflight'

ImagesFolder = r'C:\Users\username\GitHubRepository\batch-imageprocessing\test_images\images_calibration\images_raw'

ReflectanceImagesFolder = r'C:\Users\username\GitHubRepository\batch-imageprocessing\test_images\images_reflectance'

#import Micasense panel reflectance data

panelCalibration = {

"Blue": 0.61,

"Green": 0.61,

"Red": 0.61,

"Red edge": 0.60,

"NIR": 0.56

}

##############################################################################

#Calculate Radiance to Reflectance Conversion for Each Band using the Calibration Panel Images

#Need to perform manually for each band because masked panel area shifts

#PREFLIGHT CALIBRATION IMAGES

##############

#Band 1 (Blue)

#Plotting

imageName = os.path.join(CalibrationFolder_preflight, 'IMG_0002_1.tif')

imageRaw=plt.imread(imageName).T # Read raw image DN values - 16 bit tif only

plt.imshow(imageRaw.T, cmap='gray')

plotutils.colormap('viridis'); # Optional: pick a color map: 'gray, viridis, plasma, inferno, magma, nipy_spectral'

fig = plotutils.plotwithcolorbar(imageRaw.T, title='Raw image values with colorbar')

#Image metadata

meta = metadata.Metadata(imageName, exiftoolPath=exiftoolPath)

bandName = meta.get_item('XMP:BandName')

#Converting raw images to Radiance

radianceImage, L, V, R = msutils.raw_image_to_radiance(meta, imageRaw.T)

plotutils.plotwithcolorbar(V,'Vignette Factor')

plotutils.plotwithcolorbar(R,'Row Gradient Factor')

plotutils.plotwithcolorbar(V*R,'Combined Corrections')

plotutils.plotwithcolorbar(L,'Vignette and row gradient corrected raw values')

plotutils.plotwithcolorbar(radianceImage,'All factors applied and scaled to radiance')

#Mask to panel and calculate radiance

markedImg = radianceImage.copy()

ulx = 510 # upper left column (x coordinate) of panel area

uly = 350 # upper left row (y coordinate) of panel area

lrx = 710 # lower right column (x coordinate) of panel area

lry = 550 # lower right row (y coordinate) of panel area

cv2.rectangle(markedImg,(ulx,uly),(lrx,lry),(0,255,0),3)

panelRegion = radianceImage[uly:lry, ulx:lrx]

plotutils.plotwithcolorbar(markedImg, 'Panel region in radiance image')

meanRadiance = panelRegion.mean()

print('Mean Radiance in panel region: {:1.3f} W/m^2/nm/sr'.format(meanRadiance))

panelReflectance = panelCalibration[bandName]

radianceToReflectance_B1 = panelReflectance / meanRadiance

print('Radiance to reflectance conversion factor: {:1.3f}'.format(radianceToReflectance_B1))

reflectanceImage = radianceImage * radianceToReflectance_B1

plotutils.plotwithcolorbar(reflectanceImage, 'Converted Reflectane Image')

##############

#Band 2 (Green)

#Plotting

imageName = os.path.join(CalibrationFolder_preflight,'IMG_0002_2.tif')

imageRaw=plt.imread(imageName).T # Read raw image DN values - 16 bit tif only

plt.imshow(imageRaw.T, cmap='gray')

plotutils.colormap('viridis'); # Optional: pick a color map: 'gray, viridis, plasma, inferno, magma, nipy_spectral'

fig = plotutils.plotwithcolorbar(imageRaw.T, title='Raw image values with colorbar')

#Image metadata

meta = metadata.Metadata(imageName, exiftoolPath=exiftoolPath)

bandName = meta.get_item('XMP:BandName')

#Converting raw images to Radiance

radianceImage, L, V, R = msutils.raw_image_to_radiance(meta, imageRaw.T)

plotutils.plotwithcolorbar(V,'Vignette Factor')

plotutils.plotwithcolorbar(R,'Row Gradient Factor')

plotutils.plotwithcolorbar(V*R,'Combined Corrections')

plotutils.plotwithcolorbar(L,'Vignette and row gradient corrected raw values')

plotutils.plotwithcolorbar(radianceImage,'All factors applied and scaled to radiance')

#Mask to panel and calculate radiance

markedImg = radianceImage.copy()

ulx = 530 # upper left column (x coordinate) of panel area

uly = 340 # upper left row (y coordinate) of panel area

lrx = 730 # lower right column (x coordinate) of panel area

lry = 540 # lower right row (y coordinate) of panel area

cv2.rectangle(markedImg,(ulx,uly),(lrx,lry),(0,255,0),3)

panelRegion = radianceImage[uly:lry, ulx:lrx]

plotutils.plotwithcolorbar(markedImg, 'Panel region in radiance image')

meanRadiance = panelRegion.mean()

print('Mean Radiance in panel region: {:1.3f} W/m^2/nm/sr'.format(meanRadiance))

panelReflectance = panelCalibration[bandName]

radianceToReflectance_B2 = panelReflectance / meanRadiance

print('Radiance to reflectance conversion factor: {:1.3f}'.format(radianceToReflectance_B2))

reflectanceImage = radianceImage * radianceToReflectance_B2

plotutils.plotwithcolorbar(reflectanceImage, 'Converted Reflectane Image')

##############

#Band 3 (Red)

#Plotting

imageName = os.path.join(CalibrationFolder_preflight,'IMG_0002_3.tif')

imageRaw=plt.imread(imageName).T # Read raw image DN values - 16 bit tif only

plt.imshow(imageRaw.T, cmap='gray')

plotutils.colormap('viridis'); # Optional: pick a color map: 'gray, viridis, plasma, inferno, magma, nipy_spectral'

fig = plotutils.plotwithcolorbar(imageRaw.T, title='Raw image values with colorbar')

#Image metadata

meta = metadata.Metadata(imageName, exiftoolPath=exiftoolPath)

bandName = meta.get_item('XMP:BandName')

#Converting raw images to Radiance

radianceImage, L, V, R = msutils.raw_image_to_radiance(meta, imageRaw.T)

plotutils.plotwithcolorbar(V,'Vignette Factor')

plotutils.plotwithcolorbar(R,'Row Gradient Factor')

plotutils.plotwithcolorbar(V*R,'Combined Corrections')

plotutils.plotwithcolorbar(L,'Vignette and row gradient corrected raw values')

plotutils.plotwithcolorbar(radianceImage,'All factors applied and scaled to radiance')

#Mask to panel and calculate radiance

markedImg = radianceImage.copy()

ulx = 550 # upper left column (x coordinate) of panel area

uly = 300 # upper left row (y coordinate) of panel area

lrx = 750 # lower right column (x coordinate) of panel area

lry = 500 # lower right row (y coordinate) of panel area

cv2.rectangle(markedImg,(ulx,uly),(lrx,lry),(0,255,0),3)

panelRegion = radianceImage[uly:lry, ulx:lrx]

plotutils.plotwithcolorbar(markedImg, 'Panel region in radiance image')

meanRadiance = panelRegion.mean()

print('Mean Radiance in panel region: {:1.3f} W/m^2/nm/sr'.format(meanRadiance))

panelReflectance = panelCalibration[bandName]

radianceToReflectance_B3 = panelReflectance / meanRadiance

print('Radiance to reflectance conversion factor: {:1.3f}'.format(radianceToReflectance_B3))

reflectanceImage = radianceImage * radianceToReflectance_B3

plotutils.plotwithcolorbar(reflectanceImage, 'Converted Reflectane Image')

##############

#Band 4 (NIR)

#Plotting

imageName = os.path.join(CalibrationFolder_preflight,'IMG_0002_4.tif')

imageRaw=plt.imread(imageName).T # Read raw image DN values - 16 bit tif only

plt.imshow(imageRaw.T, cmap='gray')

plotutils.colormap('viridis'); # Optional: pick a color map: 'gray, viridis, plasma, inferno, magma, nipy_spectral'

fig = plotutils.plotwithcolorbar(imageRaw.T, title='Raw image values with colorbar')

#Image metadata

meta = metadata.Metadata(imageName, exiftoolPath=exiftoolPath)

bandName = meta.get_item('XMP:BandName')

#Converting raw images to Radiance

radianceImage, L, V, R = msutils.raw_image_to_radiance(meta, imageRaw.T)

plotutils.plotwithcolorbar(V,'Vignette Factor')

plotutils.plotwithcolorbar(R,'Row Gradient Factor')

plotutils.plotwithcolorbar(V*R,'Combined Corrections')

plotutils.plotwithcolorbar(L,'Vignette and row gradient corrected raw values')

plotutils.plotwithcolorbar(radianceImage,'All factors applied and scaled to radiance')

#Mask to panel and calculate radiance

markedImg = radianceImage.copy()

ulx = 510 # upper left column (x coordinate) of panel area

uly = 330 # upper left row (y coordinate) of panel area

lrx = 710 # lower right column (x coordinate) of panel area

lry = 530 # lower right row (y coordinate) of panel area

cv2.rectangle(markedImg,(ulx,uly),(lrx,lry),(0,255,0),3)

panelRegion = radianceImage[uly:lry, ulx:lrx]

plotutils.plotwithcolorbar(markedImg, 'Panel region in radiance image')

meanRadiance = panelRegion.mean()

print('Mean Radiance in panel region: {:1.3f} W/m^2/nm/sr'.format(meanRadiance))

panelReflectance = panelCalibration[bandName]

radianceToReflectance_B4 = panelReflectance / meanRadiance

print('Radiance to reflectance conversion factor: {:1.3f}'.format(radianceToReflectance_B4))

reflectanceImage = radianceImage * radianceToReflectance_B4

plotutils.plotwithcolorbar(reflectanceImage, 'Converted Reflectane Image')

##############

#Band 5 (Red edge)

#Plotting

imageName = os.path.join(CalibrationFolder_preflight,'IMG_0002_5.tif')

imageRaw=plt.imread(imageName).T # Read raw image DN values - 16 bit tif only

plt.imshow(imageRaw.T, cmap='gray')

plotutils.colormap('viridis'); # Optional: pick a color map: 'gray, viridis, plasma, inferno, magma, nipy_spectral'

fig = plotutils.plotwithcolorbar(imageRaw.T, title='Raw image values with colorbar')

#Image metadata

meta = metadata.Metadata(imageName, exiftoolPath=exiftoolPath)

bandName = meta.get_item('XMP:BandName')

#Converting raw images to Radiance

radianceImage, L, V, R = msutils.raw_image_to_radiance(meta, imageRaw.T)

plotutils.plotwithcolorbar(V,'Vignette Factor')

plotutils.plotwithcolorbar(R,'Row Gradient Factor')

plotutils.plotwithcolorbar(V*R,'Combined Corrections')

plotutils.plotwithcolorbar(L,'Vignette and row gradient corrected raw values')

plotutils.plotwithcolorbar(radianceImage,'All factors applied and scaled to radiance')

#Mask to panel and calculate radiance

markedImg = radianceImage.copy()

ulx = 520 # upper left column (x coordinate) of panel area

uly = 320 # upper left row (y coordinate) of panel area

lrx = 720 # lower right column (x coordinate) of panel area

lry = 520 # lower right row (y coordinate) of panel area

cv2.rectangle(markedImg,(ulx,uly),(lrx,lry),(0,255,0),3)

panelRegion = radianceImage[uly:lry, ulx:lrx]

plotutils.plotwithcolorbar(markedImg, 'Panel region in radiance image')

meanRadiance = panelRegion.mean()

print('Mean Radiance in panel region: {:1.3f} W/m^2/nm/sr'.format(meanRadiance))

panelReflectance = panelCalibration[bandName]

radianceToReflectance_B5 = panelReflectance / meanRadiance

print('Radiance to reflectance conversion factor: {:1.3f}'.format(radianceToReflectance_B5))

reflectanceImage = radianceImage * radianceToReflectance_B5

plotutils.plotwithcolorbar(reflectanceImage, 'Converted Reflectane Image')

#Check Radiance to Reflectance conversion for each band

print('Blue: {:1.3f}'.format(radianceToReflectance_B1))

print('Green: {:1.3f}'.format(radianceToReflectance_B2))

print('Red: {:1.3f}'.format(radianceToReflectance_B3))

print('NIR: {:1.3f}'.format(radianceToReflectance_B4))

print('Red edge: {:1.3f}'.format(radianceToReflectance_B5))

#POSTFLIGHT

##############################################################################

#Calculate Radiance to Reflectance Conversion for Each Band using the Calibration Panel Images

##############

#Band 1 (Blue)

#Plotting

imageName = os.path.join(CalibrationFolder_postflight,'IMG_0119_1.tif')

imageRaw=plt.imread(imageName).T # Read raw image DN values - 16 bit tif only

plt.imshow(imageRaw.T, cmap='gray')

plotutils.colormap('viridis'); # Optional: pick a color map: 'gray, viridis, plasma, inferno, magma, nipy_spectral'

fig = plotutils.plotwithcolorbar(imageRaw.T, title='Raw image values with colorbar')

#Image metadata

meta = metadata.Metadata(imageName, exiftoolPath=exiftoolPath)

bandName = meta.get_item('XMP:BandName')

#Converting raw images to Radiance

radianceImage, L, V, R = msutils.raw_image_to_radiance(meta, imageRaw.T)

plotutils.plotwithcolorbar(V,'Vignette Factor')

plotutils.plotwithcolorbar(R,'Row Gradient Factor')

plotutils.plotwithcolorbar(V*R,'Combined Corrections')

plotutils.plotwithcolorbar(L,'Vignette and row gradient corrected raw values')

plotutils.plotwithcolorbar(radianceImage,'All factors applied and scaled to radiance')

#Mask to panel and calculate radiance

markedImg = radianceImage.copy()

ulx = 460 # upper left column (x coordinate) of panel area

uly = 550 # upper left row (y coordinate) of panel area

lrx = 600 # lower right column (x coordinate) of panel area

lry = 700 # lower right row (y coordinate) of panel area

cv2.rectangle(markedImg,(ulx,uly),(lrx,lry),(0,255,0),3)

panelRegion = radianceImage[uly:lry, ulx:lrx]

plotutils.plotwithcolorbar(markedImg, 'Panel region in radiance image')

meanRadiance = panelRegion.mean()

print('Mean Radiance in panel region: {:1.3f} W/m^2/nm/sr'.format(meanRadiance))

panelReflectance = panelCalibration[bandName]

radianceToReflectance_B1_post = panelReflectance / meanRadiance

print('Radiance to reflectance conversion factor: {:1.3f}'.format(radianceToReflectance_B1_post))

reflectanceImage = radianceImage * radianceToReflectance_B1_post

plotutils.plotwithcolorbar(reflectanceImage, 'Converted Reflectane Image')

##############

#Band 2 (Green)

#Plotting

imageName = os.path.join(CalibrationFolder_postflight,'IMG_0119_2.tif')

imageRaw=plt.imread(imageName).T # Read raw image DN values - 16 bit tif only

plt.imshow(imageRaw.T, cmap='gray')

plotutils.colormap('viridis'); # Optional: pick a color map: 'gray, viridis, plasma, inferno, magma, nipy_spectral'

fig = plotutils.plotwithcolorbar(imageRaw.T, title='Raw image values with colorbar')

#Image metadata

meta = metadata.Metadata(imageName, exiftoolPath=exiftoolPath)

bandName = meta.get_item('XMP:BandName')

#Converting raw images to Radiance

radianceImage, L, V, R = msutils.raw_image_to_radiance(meta, imageRaw.T)

plotutils.plotwithcolorbar(V,'Vignette Factor')

plotutils.plotwithcolorbar(R,'Row Gradient Factor')

plotutils.plotwithcolorbar(V*R,'Combined Corrections')

plotutils.plotwithcolorbar(L,'Vignette and row gradient corrected raw values')

plotutils.plotwithcolorbar(radianceImage,'All factors applied and scaled to radiance')

#Mask to panel and calculate radiance

markedImg = radianceImage.copy()

ulx = 470 # upper left column (x coordinate) of panel area

uly = 540 # upper left row (y coordinate) of panel area

lrx = 610 # lower right column (x coordinate) of panel area

lry = 690 # lower right row (y coordinate) of panel area

cv2.rectangle(markedImg,(ulx,uly),(lrx,lry),(0,255,0),3)

panelRegion = radianceImage[uly:lry, ulx:lrx]

plotutils.plotwithcolorbar(markedImg, 'Panel region in radiance image')

meanRadiance = panelRegion.mean()

print('Mean Radiance in panel region: {:1.3f} W/m^2/nm/sr'.format(meanRadiance))

panelReflectance = panelCalibration[bandName]

radianceToReflectance_B2_post = panelReflectance / meanRadiance

print('Radiance to reflectance conversion factor: {:1.3f}'.format(radianceToReflectance_B2_post))

reflectanceImage = radianceImage * radianceToReflectance_B2_post

plotutils.plotwithcolorbar(reflectanceImage, 'Converted Reflectane Image')

##############

#Band 3 (Red)

#Plotting

imageName = os.path.join(CalibrationFolder_postflight,'IMG_0119_3.tif')

imageRaw=plt.imread(imageName).T # Read raw image DN values - 16 bit tif only

plt.imshow(imageRaw.T, cmap='gray')

plotutils.colormap('viridis'); # Optional: pick a color map: 'gray, viridis, plasma, inferno, magma, nipy_spectral'

fig = plotutils.plotwithcolorbar(imageRaw.T, title='Raw image values with colorbar')

#Image metadata

meta = metadata.Metadata(imageName, exiftoolPath=exiftoolPath)

bandName = meta.get_item('XMP:BandName')

#Converting raw images to Radiance

radianceImage, L, V, R = msutils.raw_image_to_radiance(meta, imageRaw.T)

plotutils.plotwithcolorbar(V,'Vignette Factor')

plotutils.plotwithcolorbar(R,'Row Gradient Factor')

plotutils.plotwithcolorbar(V*R,'Combined Corrections')

plotutils.plotwithcolorbar(L,'Vignette and row gradient corrected raw values')

plotutils.plotwithcolorbar(radianceImage,'All factors applied and scaled to radiance')

#Mask to panel and calculate radiance

markedImg = radianceImage.copy()

ulx = 480 # upper left column (x coordinate) of panel area

uly = 520 # upper left row (y coordinate) of panel area

lrx = 620 # lower right column (x coordinate) of panel area

lry = 670 # lower right row (y coordinate) of panel area

cv2.rectangle(markedImg,(ulx,uly),(lrx,lry),(0,255,0),3)

panelRegion = radianceImage[uly:lry, ulx:lrx]

plotutils.plotwithcolorbar(markedImg, 'Panel region in radiance image')

meanRadiance = panelRegion.mean()

print('Mean Radiance in panel region: {:1.3f} W/m^2/nm/sr'.format(meanRadiance))

panelReflectance = panelCalibration[bandName]

radianceToReflectance_B3_post = panelReflectance / meanRadiance

print('Radiance to reflectance conversion factor: {:1.3f}'.format(radianceToReflectance_B3_post))

reflectanceImage = radianceImage * radianceToReflectance_B3_post

plotutils.plotwithcolorbar(reflectanceImage, 'Converted Reflectane Image')

##############

#Band 4 (NIR)

#Plotting

imageName = os.path.join(CalibrationFolder_postflight,'IMG_0119_4.tif')

imageRaw=plt.imread(imageName).T # Read raw image DN values - 16 bit tif only

plt.imshow(imageRaw.T, cmap='gray')

plotutils.colormap('viridis'); # Optional: pick a color map: 'gray, viridis, plasma, inferno, magma, nipy_spectral'

fig = plotutils.plotwithcolorbar(imageRaw.T, title='Raw image values with colorbar')

#Image metadata

meta = metadata.Metadata(imageName, exiftoolPath=exiftoolPath)

bandName = meta.get_item('XMP:BandName')

#Converting raw images to Radiance

radianceImage, L, V, R = msutils.raw_image_to_radiance(meta, imageRaw.T)

plotutils.plotwithcolorbar(V,'Vignette Factor')

plotutils.plotwithcolorbar(R,'Row Gradient Factor')

plotutils.plotwithcolorbar(V*R,'Combined Corrections')

plotutils.plotwithcolorbar(L,'Vignette and row gradient corrected raw values')

plotutils.plotwithcolorbar(radianceImage,'All factors applied and scaled to radiance')

#Mask to panel and calculate radiance

markedImg = radianceImage.copy()

ulx = 460 # upper left column (x coordinate) of panel area

uly = 530 # upper left row (y coordinate) of panel area

lrx = 600 # lower right column (x coordinate) of panel area

lry = 680 # lower right row (y coordinate) of panel area

cv2.rectangle(markedImg,(ulx,uly),(lrx,lry),(0,255,0),3)

panelRegion = radianceImage[uly:lry, ulx:lrx]

plotutils.plotwithcolorbar(markedImg, 'Panel region in radiance image')

meanRadiance = panelRegion.mean()

print('Mean Radiance in panel region: {:1.3f} W/m^2/nm/sr'.format(meanRadiance))

panelReflectance = panelCalibration[bandName]

radianceToReflectance_B4_post = panelReflectance / meanRadiance

print('Radiance to reflectance conversion factor: {:1.3f}'.format(radianceToReflectance_B4_post))

reflectanceImage = radianceImage * radianceToReflectance_B4_post

plotutils.plotwithcolorbar(reflectanceImage, 'Converted Reflectane Image')

##############

#Band 5 (Red edge)

#Plotting

imageName = os.path.join(CalibrationFolder_postflight,'IMG_0119_5.tif')

imageRaw=plt.imread(imageName).T # Read raw image DN values - 16 bit tif only

plt.imshow(imageRaw.T, cmap='gray')

plotutils.colormap('viridis'); # Optional: pick a color map: 'gray, viridis, plasma, inferno, magma, nipy_spectral'

fig = plotutils.plotwithcolorbar(imageRaw.T, title='Raw image values with colorbar')

#Image metadata

meta = metadata.Metadata(imageName, exiftoolPath=exiftoolPath)

bandName = meta.get_item('XMP:BandName')

#Converting raw images to Radiance

radianceImage, L, V, R = msutils.raw_image_to_radiance(meta, imageRaw.T)

plotutils.plotwithcolorbar(V,'Vignette Factor')

plotutils.plotwithcolorbar(R,'Row Gradient Factor')

plotutils.plotwithcolorbar(V*R,'Combined Corrections')

plotutils.plotwithcolorbar(L,'Vignette and row gradient corrected raw values')

plotutils.plotwithcolorbar(radianceImage,'All factors applied and scaled to radiance')

#Mask to panel and calculate radiance

markedImg = radianceImage.copy()

ulx = 470 # upper left column (x coordinate) of panel area

uly = 520 # upper left row (y coordinate) of panel area

lrx = 610 # lower right column (x coordinate) of panel area

lry = 670 # lower right row (y coordinate) of panel area

cv2.rectangle(markedImg,(ulx,uly),(lrx,lry),(0,255,0),3)

panelRegion = radianceImage[uly:lry, ulx:lrx]

plotutils.plotwithcolorbar(markedImg, 'Panel region in radiance image')

meanRadiance = panelRegion.mean()

print('Mean Radiance in panel region: {:1.3f} W/m^2/nm/sr'.format(meanRadiance))

panelReflectance = panelCalibration[bandName]

radianceToReflectance_B5_post = panelReflectance / meanRadiance

print('Radiance to reflectance conversion factor: {:1.3f}'.format(radianceToReflectance_B5_post))

reflectanceImage = radianceImage * radianceToReflectance_B5_post

plotutils.plotwithcolorbar(reflectanceImage, 'Converted Reflectane Image')

#Check Radiance to Reflectance conversion for each band

print('Blue: {:1.3f}'.format(radianceToReflectance_B1_post))

print('Green: {:1.3f}'.format(radianceToReflectance_B2_post))

print('Red: {:1.3f}'.format(radianceToReflectance_B3_post))

print('NIR: {:1.3f}'.format(radianceToReflectance_B4_post))

print('Red edge: {:1.3f}'.format(radianceToReflectance_B5_post))

#################################################################

#AVG Pre and Post Flight Calibration

#Check Radiance to Reflectance conversion for each band

radianceToReflectance_B1_avg = (radianceToReflectance_B1 + radianceToReflectance_B1_post)/2

radianceToReflectance_B2_avg = (radianceToReflectance_B2 + radianceToReflectance_B2_post)/2

radianceToReflectance_B3_avg = (radianceToReflectance_B3 + radianceToReflectance_B3_post)/2

radianceToReflectance_B4_avg = (radianceToReflectance_B4 + radianceToReflectance_B4_post)/2

radianceToReflectance_B5_avg = (radianceToReflectance_B5 + radianceToReflectance_B5_post)/2

##############################################################################

##############################################################################

#Part 2

#Write function to read band

def get_band(image):

meta = metadata.Metadata(image, exiftoolPath=exiftoolPath)

band = meta.get_item('XMP:BandName')

return band

#Begin loop to process raw images to reflectance

for image in os.listdir(ImagesFolder):

#Ignore all but TIF

if os.path.splitext(image)[-1] == ".tif":

#Read images and get metadata

imagepath = os.path.join(ImagesFolder, image)

band = get_band(imagepath)

meta = metadata.Metadata(imagepath, exiftoolPath=exiftoolPath)

ImageRaw=plt.imread(imagepath)

#Convert DN to Radiance

flightRadianceImage, _, _, _ = msutils.raw_image_to_radiance(meta, ImageRaw)

#plotutils.plotwithcolorbar(flightRadianceImage, 'Radiance Image')

#Convert Radiance to Reflectance

if band == "Blue":

flightReflectanceImage = flightRadianceImage * radianceToReflectance_B1_avg

elif band == "Green":

flightReflectanceImage = flightRadianceImage * radianceToReflectance_B2_avg

elif band == "Red":

flightReflectanceImage = flightRadianceImage * radianceToReflectance_B3_avg

elif band == "NIR":

flightReflectanceImage = flightRadianceImage * radianceToReflectance_B4_avg

elif band == "Red edge":

flightReflectanceImage = flightRadianceImage * radianceToReflectance_B5_avg

else:

print("error")

#Export TIFF

if not os.path.exists(ReflectanceImagesFolder):

os.makedirs(ReflectanceImagesFolder)

outfile = os.path.join(ReflectanceImagesFolder, image)

im = Image.fromarray(flightReflectanceImage)

im.save(outfile)

#End loop

#############################################################################

#############################################################################

#Part 3

#Transfer metadata

#Pathways must not have spaces

#Copy the following to the command prompt

#exiftool -tagsFromFile C:\Users\username\GitHubRepository\batch-imageprocessing\test_images\images_calibration\images_raw\%f.tif -file:all -iptc:all -exif:all -xmp -Composite:all C:\Users\username\GitHubRepository\batch-imageprocessing\test_images\images_reflectance -overwrite_original