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flirRawToTemperature to use shutter temperature #37

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flirRawToTemperature to use shutter temperature #37

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86 changes: 57 additions & 29 deletions flir2tif/Get_FLIR.py
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Original file line number Diff line number Diff line change
Expand Up @@ -45,7 +45,7 @@ def __init__(self):
self.calibrationX = 0.0
self.calibrationb1 = 0.0
self.calibrationb2 = 0.0

self.shuttertemperature = 0.0

def options():

Expand Down Expand Up @@ -185,6 +185,7 @@ def get_calibrate_param(metadata):
try:
if 'terraref_cleaned_metadata' in metadata:
fixedmd = metadata['sensor_fixed_metadata']
sensor_variable_meta = metadata['sensor_variable_metadata']
if fixedmd['is_calibrated'] == 'True':
return calibparameter
else:
Expand All @@ -199,6 +200,7 @@ def get_calibrate_param(metadata):
calibparameter.calibrationX = float(fixedmd['calibration_X'])
calibparameter.calibrationb1 = float(fixedmd['calibration_beta1'])
calibparameter.calibrationb2 = float(fixedmd['calibration_beta2'])
calibparameter.shuttertemperature = float(sensor_variable_meta['shutter_temperature_[K]'])
return calibparameter

except KeyError as err:
Expand Down Expand Up @@ -302,59 +304,85 @@ def flir_data_visualization(im, outfile_path, Gmin, Gmax):
return np.array(img_data)

# convert flir raw data into temperature C degree, for date after September 15th
# code converted from Matlab https://github.com/terraref/computing-pipeline/blob/master/scripts/FLIR/FlirRawToTemperature.m
def flirRawToTemperature(rawData, calibP):

R = calibP.calibrationR
B = calibP.calibrationB
F = calibP.calibrationF
J0 = calibP.calibrationJ0
J1 = calibP.calibrationJ1


# Constant camera-specific parameters determined by FLIR
# Plank constant - Flir
R = calibP.calibrationR # function of integration time and wavelength
B = calibP.calibrationB # function of wavelength
F = calibP.calibrationF # positive value (0 - 1)
J0 = calibP.calibrationJ0 # global offset
J1 = calibP.calibrationJ1 # global gain

# Constant Atmospheric transmission parameter by Flir
X = calibP.calibrationX
a1 = calibP.calibrationa1
b1 = calibP.calibrationb1
a2 = calibP.calibrationa2
b2 = calibP.calibrationb2


# Constant for VPD computation (sqtrH2O)
H2O_K1 = 1.56
H2O_K2 = 0.0694
H2O_K3 = -0.000278
H2O_K4 = 0.000000685

H = 0.1
T = 22.0
D = 2.5
E = 0.98

K0 = 273.15


K0 = 273.15 # Kelvin to Celsius temperature constant

# Environmental factors
H = 0.1 # Relative Humidity from the gantry (0 - 1)
T = calibP.shuttertemperature - K0 # air temperature in degree Celsius from the gantry
D = 2.5 # ObjectDistance - camera/canopy (m)
E = 0.98 # bject emissivity, vegetation is around 0.98, bare soil around 0.93...

im = rawData

AmbTemp = T + K0
AtmTemp = T + K0


# Step 1: Atmospheric transmission - correction factor from air temp, relative humidity and distance sensor-object;
# Vapour pressure deficit call here sqrtH2O => convert relative humidity and air temperature in VPD - mmHg - 1mmHg=0.133 322 39 kPa
H2OInGperM2 = H*math.exp(H2O_K1 + H2O_K2*T + H2O_K3*math.pow(T, 2) + H2O_K4*math.pow(T, 3))
# Atmospheric transmission correction: tao
a1b1sqH2O = (a1+b1*math.sqrt(H2OInGperM2))
a2b2sqH2O = (a2+b2*math.sqrt(H2OInGperM2))
exp1 = math.exp(-math.sqrt(D/2)*a1b1sqH2O)
exp2 = math.exp(-math.sqrt(D/2)*a2b2sqH2O)

tao = X*exp1 + (1-X)*exp2

obj_rad = im*E*tao

tao = X*exp1 + (1-X)*exp2 # Atmospheric transmission factor

# Step2: Correct raw pixel values from external factors
# General equation : Total Radiation = Object Radiation + Atmosphere Radiation + Ambient Reflection Radiation

# Object Radiation: obj_rad
# obj_rad = Theoretical object radiation * emissivity * atmospheric transmission
obj_rad = im*E*tao # For each pixel

# Theoretical atmospheric radiation: theo_atm_rad
theo_atm_rad = (R*J1/(math.exp(B/AtmTemp)-F)) + J0
atm_rad = repmat((1-tao)*theo_atm_rad, 640, 480)


# Atmosphere Radiation: atm_rad
# atm_rad = (1 - atmospheric transmission) * Theoretical atmospheric radiation
atm_rad = repmat((1-tao)*theo_atm_rad, 480, 640)

# Theoretical Ambient Reflection Radiation: theo_amb_refl_rad
theo_amb_refl_rad = (R*J1/(math.exp(B/AmbTemp)-F)) + J0
amb_refl_rad = repmat((1-E)*tao*theo_amb_refl_rad, 640, 480)


# Ambient Reflection Radiation: amb_refl_rad
# amb_refl_rad = (1 - emissivity) * atmospheric transmission * Theoretical Ambient Reflection Radiation
amb_refl_rad = repmat((1-E)*tao*theo_amb_refl_rad, 480, 640)

# Total Radiation: corr_pxl_val
corr_pxl_val = obj_rad + atm_rad + amb_refl_rad

pxl_temp = B/np.log(R/(corr_pxl_val-J0)*J1+F)

# Step 3:RBF equation: transformation of pixel intensity in radiometric temperature from raw values or
# corrected values (in degree Celsius)
pxl_temp = B/np.log(R/(corr_pxl_val-J0)*J1+F) - K0 # for each pixel

return pxl_temp


def get_bounding_box(center_position, fov):
# NOTE: ZERO_ZERO is the southeast corner of the field. Position values increase to the northwest (so +y-position = +latitude, or more north and +x-position = -longitude, or more west)
# We are also simplifying the conversion of meters to decimal degrees since we're not close to the poles and working with small distances.
Expand Down