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Python/digital_image_processing/index_calculation.py

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add the index calculation class at digital_image_processing and the hamming code algorithm at hashes (#1152) * add the index calculation at difital_image_processing file * make changes at index_calculation * update the variables to self variables at functions * update the word wrap in comments at index_calculation * add the hamming code algorithm * Wrap long lines
2019-12-06 06:13:10 +00:00
# Author: João Gustavo A. Amorim
# Author email: joaogustavoamorim@gmail.com
# Coding date: jan 2019
# python/black: True
# Imports
import numpy as np
# Class implemented to calculus the index
class IndexCalculation:
"""
# Class Summary
This algorithm consists in calculating vegetation indices, these indices
can be used for precision agriculture for example (or remote sensing). There are
functions to define the data and to calculate the implemented indices.
# Vegetation index
https://en.wikipedia.org/wiki/Vegetation_Index
A Vegetation Index (VI) is a spectral transformation of two or more bands designed
to enhance the contribution of vegetation properties and allow reliable spatial and
temporal inter-comparisons of terrestrial photosynthetic activity and canopy
structural variations
# Information about channels (Wavelength range for each)
* nir - near-infrared
https://www.malvernpanalytical.com/br/products/technology/near-infrared-spectroscopy
Wavelength Range 700 nm to 2500 nm
* Red Edge
https://en.wikipedia.org/wiki/Red_edge
Wavelength Range 680 nm to 730 nm
* red
https://en.wikipedia.org/wiki/Color
Wavelength Range 635 nm to 700 nm
* blue
https://en.wikipedia.org/wiki/Color
Wavelength Range 450 nm to 490 nm
* green
https://en.wikipedia.org/wiki/Color
Wavelength Range 520 nm to 560 nm
# Implemented index list
#"abbreviationOfIndexName" -- list of channels used
#"ARVI2" -- red, nir
#"CCCI" -- red, redEdge, nir
#"CVI" -- red, green, nir
#"GLI" -- red, green, blue
#"NDVI" -- red, nir
#"BNDVI" -- blue, nir
#"redEdgeNDVI" -- red, redEdge
#"GNDVI" -- green, nir
#"GBNDVI" -- green, blue, nir
#"GRNDVI" -- red, green, nir
#"RBNDVI" -- red, blue, nir
#"PNDVI" -- red, green, blue, nir
#"ATSAVI" -- red, nir
#"BWDRVI" -- blue, nir
#"CIgreen" -- green, nir
#"CIrededge" -- redEdge, nir
#"CI" -- red, blue
#"CTVI" -- red, nir
#"GDVI" -- green, nir
#"EVI" -- red, blue, nir
#"GEMI" -- red, nir
#"GOSAVI" -- green, nir
#"GSAVI" -- green, nir
#"Hue" -- red, green, blue
#"IVI" -- red, nir
#"IPVI" -- red, nir
#"I" -- red, green, blue
#"RVI" -- red, nir
#"MRVI" -- red, nir
#"MSAVI" -- red, nir
#"NormG" -- red, green, nir
#"NormNIR" -- red, green, nir
#"NormR" -- red, green, nir
#"NGRDI" -- red, green
#"RI" -- red, green
#"S" -- red, green, blue
#"IF" -- red, green, blue
#"DVI" -- red, nir
#"TVI" -- red, nir
#"NDRE" -- redEdge, nir
#list of all index implemented
#allIndex = ["ARVI2", "CCCI", "CVI", "GLI", "NDVI", "BNDVI", "redEdgeNDVI", "GNDVI",
"GBNDVI", "GRNDVI", "RBNDVI", "PNDVI", "ATSAVI", "BWDRVI", "CIgreen",
"CIrededge", "CI", "CTVI", "GDVI", "EVI", "GEMI", "GOSAVI", "GSAVI",
"Hue", "IVI", "IPVI", "I", "RVI", "MRVI", "MSAVI", "NormG", "NormNIR",
"NormR", "NGRDI", "RI", "S", "IF", "DVI", "TVI", "NDRE"]
#list of index with not blue channel
#notBlueIndex = ["ARVI2", "CCCI", "CVI", "NDVI", "redEdgeNDVI", "GNDVI", "GRNDVI",
"ATSAVI", "CIgreen", "CIrededge", "CTVI", "GDVI", "GEMI", "GOSAVI",
"GSAVI", "IVI", "IPVI", "RVI", "MRVI", "MSAVI", "NormG", "NormNIR",
"NormR", "NGRDI", "RI", "DVI", "TVI", "NDRE"]
#list of index just with RGB channels
#RGBIndex = ["GLI", "CI", "Hue", "I", "NGRDI", "RI", "S", "IF"]
"""
def __init__(self, red=None, green=None, blue=None, redEdge=None, nir=None):
# print("Numpy version: " + np.__version__)
self.setMatrices(red=red, green=green, blue=blue, redEdge=redEdge, nir=nir)
def setMatrices(self, red=None, green=None, blue=None, redEdge=None, nir=None):
if red is not None:
self.red = red
if green is not None:
self.green = green
if blue is not None:
self.blue = blue
if redEdge is not None:
self.redEdge = redEdge
if nir is not None:
self.nir = nir
return True
def calculation(
self, index="", red=None, green=None, blue=None, redEdge=None, nir=None
):
"""
performs the calculation of the index with the values instantiated in the class
:str index: abbreviation of index name to perform
"""
self.setMatrices(red=red, green=green, blue=blue, redEdge=redEdge, nir=nir)
funcs = {
"ARVI2": self.ARVI2,
"CCCI": self.CCCI,
"CVI": self.CVI,
"GLI": self.GLI,
"NDVI": self.NDVI,
"BNDVI": self.BNDVI,
"redEdgeNDVI": self.redEdgeNDVI,
"GNDVI": self.GNDVI,
"GBNDVI": self.GBNDVI,
"GRNDVI": self.GRNDVI,
"RBNDVI": self.RBNDVI,
"PNDVI": self.PNDVI,
"ATSAVI": self.ATSAVI,
"BWDRVI": self.BWDRVI,
"CIgreen": self.CIgreen,
"CIrededge": self.CIrededge,
"CI": self.CI,
"CTVI": self.CTVI,
"GDVI": self.GDVI,
"EVI": self.EVI,
"GEMI": self.GEMI,
"GOSAVI": self.GOSAVI,
"GSAVI": self.GSAVI,
"Hue": self.Hue,
"IVI": self.IVI,
"IPVI": self.IPVI,
"I": self.I,
"RVI": self.RVI,
"MRVI": self.MRVI,
"MSAVI": self.MSAVI,
"NormG": self.NormG,
"NormNIR": self.NormNIR,
"NormR": self.NormR,
"NGRDI": self.NGRDI,
"RI": self.RI,
"S": self.S,
"IF": self.IF,
"DVI": self.DVI,
"TVI": self.TVI,
"NDRE": self.NDRE,
}
try:
return funcs[index]()
except KeyError:
print("Index not in the list!")
return False
def ARVI2(self):
"""
improved prime numbers implementation (#1606) * improved prime numbers implementation * fixup! Format Python code with psf/black push * fix type hint * fixup! Format Python code with psf/black push * fix doctests * updating DIRECTORY.md * added prime tests with negative numbers * using for instead filter * updating DIRECTORY.md * Remove unused typing.List * Remove tab indentation * print("Sorted order is:", " ".join(a))
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Atmospherically Resistant Vegetation Index 2
https://www.indexdatabase.de/db/i-single.php?id=396
:return: index
−0.18+1.17*(self.nir−self.red)/(self.nir+self.red)
add the index calculation class at digital_image_processing and the hamming code algorithm at hashes (#1152) * add the index calculation at difital_image_processing file * make changes at index_calculation * update the variables to self variables at functions * update the word wrap in comments at index_calculation * add the hamming code algorithm * Wrap long lines
2019-12-06 06:13:10 +00:00
"""
return -0.18 + (1.17 * ((self.nir - self.red) / (self.nir + self.red)))
def CCCI(self):
"""
Canopy Chlorophyll Content Index
https://www.indexdatabase.de/db/i-single.php?id=224
:return: index
"""
return ((self.nir - self.redEdge) / (self.nir + self.redEdge)) / (
(self.nir - self.red) / (self.nir + self.red)
)
def CVI(self):
"""
Chlorophyll vegetation index
https://www.indexdatabase.de/db/i-single.php?id=391
:return: index
"""
return self.nir * (self.red / (self.green ** 2))
def GLI(self):
"""
self.green leaf index
https://www.indexdatabase.de/db/i-single.php?id=375
:return: index
"""
return (2 * self.green - self.red - self.blue) / (
2 * self.green + self.red + self.blue
)
def NDVI(self):
"""
Normalized Difference self.nir/self.red Normalized Difference Vegetation Index,
Calibrated NDVI - CDVI
https://www.indexdatabase.de/db/i-single.php?id=58
:return: index
"""
return (self.nir - self.red) / (self.nir + self.red)
def BNDVI(self):
"""
Normalized Difference self.nir/self.blue self.blue-normalized difference
vegetation index
https://www.indexdatabase.de/db/i-single.php?id=135
:return: index
"""
return (self.nir - self.blue) / (self.nir + self.blue)
def redEdgeNDVI(self):
"""
Normalized Difference self.rededge/self.red
https://www.indexdatabase.de/db/i-single.php?id=235
:return: index
"""
return (self.redEdge - self.red) / (self.redEdge + self.red)
def GNDVI(self):
"""
Normalized Difference self.nir/self.green self.green NDVI
https://www.indexdatabase.de/db/i-single.php?id=401
:return: index
"""
return (self.nir - self.green) / (self.nir + self.green)
def GBNDVI(self):
"""
self.green-self.blue NDVI
https://www.indexdatabase.de/db/i-single.php?id=186
:return: index
"""
return (self.nir - (self.green + self.blue)) / (
self.nir + (self.green + self.blue)
)
def GRNDVI(self):
"""
self.green-self.red NDVI
https://www.indexdatabase.de/db/i-single.php?id=185
:return: index
"""
return (self.nir - (self.green + self.red)) / (
self.nir + (self.green + self.red)
)
def RBNDVI(self):
"""
self.red-self.blue NDVI
https://www.indexdatabase.de/db/i-single.php?id=187
:return: index
"""
return (self.nir - (self.blue + self.red)) / (self.nir + (self.blue + self.red))
def PNDVI(self):
"""
Pan NDVI
https://www.indexdatabase.de/db/i-single.php?id=188
:return: index
"""
return (self.nir - (self.green + self.red + self.blue)) / (
self.nir + (self.green + self.red + self.blue)
)
def ATSAVI(self, X=0.08, a=1.22, b=0.03):
"""
Adjusted transformed soil-adjusted VI
https://www.indexdatabase.de/db/i-single.php?id=209
:return: index
"""
return a * (
(self.nir - a * self.red - b)
/ (a * self.nir + self.red - a * b + X * (1 + a ** 2))
)
def BWDRVI(self):
"""
self.blue-wide dynamic range vegetation index
https://www.indexdatabase.de/db/i-single.php?id=136
:return: index
"""
return (0.1 * self.nir - self.blue) / (0.1 * self.nir + self.blue)
def CIgreen(self):
"""
Chlorophyll Index self.green
https://www.indexdatabase.de/db/i-single.php?id=128
:return: index
"""
return (self.nir / self.green) - 1
def CIrededge(self):
"""
Chlorophyll Index self.redEdge
https://www.indexdatabase.de/db/i-single.php?id=131
:return: index
"""
return (self.nir / self.redEdge) - 1
def CI(self):
"""
Coloration Index
https://www.indexdatabase.de/db/i-single.php?id=11
:return: index
"""
return (self.red - self.blue) / self.red
def CTVI(self):
"""
Corrected Transformed Vegetation Index
https://www.indexdatabase.de/db/i-single.php?id=244
:return: index
"""
ndvi = self.NDVI()
return ((ndvi + 0.5) / (abs(ndvi + 0.5))) * (abs(ndvi + 0.5) ** (1 / 2))
def GDVI(self):
"""
Difference self.nir/self.green self.green Difference Vegetation Index
https://www.indexdatabase.de/db/i-single.php?id=27
:return: index
"""
return self.nir - self.green
def EVI(self):
"""
Enhanced Vegetation Index
https://www.indexdatabase.de/db/i-single.php?id=16
:return: index
"""
return 2.5 * (
(self.nir - self.red) / (self.nir + 6 * self.red - 7.5 * self.blue + 1)
)
def GEMI(self):
"""
Global Environment Monitoring Index
https://www.indexdatabase.de/db/i-single.php?id=25
:return: index
"""
n = (2 * (self.nir ** 2 - self.red ** 2) + 1.5 * self.nir + 0.5 * self.red) / (
self.nir + self.red + 0.5
)
return n * (1 - 0.25 * n) - (self.red - 0.125) / (1 - self.red)
def GOSAVI(self, Y=0.16):
"""
self.green Optimized Soil Adjusted Vegetation Index
https://www.indexdatabase.de/db/i-single.php?id=29
mit Y = 0,16
:return: index
"""
return (self.nir - self.green) / (self.nir + self.green + Y)
def GSAVI(self, L=0.5):
"""
self.green Soil Adjusted Vegetation Index
https://www.indexdatabase.de/db/i-single.php?id=31
mit L = 0,5
:return: index
"""
return ((self.nir - self.green) / (self.nir + self.green + L)) * (1 + L)
def Hue(self):
"""
Hue
https://www.indexdatabase.de/db/i-single.php?id=34
:return: index
"""
return np.arctan(
pyupgrade --py37-plus **/*.py (#1654) * pyupgrade --py37-plus **/*.py * fixup! Format Python code with psf/black push
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((2 * self.red - self.green - self.blue) / 30.5) * (self.green - self.blue)
add the index calculation class at digital_image_processing and the hamming code algorithm at hashes (#1152) * add the index calculation at difital_image_processing file * make changes at index_calculation * update the variables to self variables at functions * update the word wrap in comments at index_calculation * add the hamming code algorithm * Wrap long lines
2019-12-06 06:13:10 +00:00
)
def IVI(self, a=None, b=None):
"""
Ideal vegetation index
https://www.indexdatabase.de/db/i-single.php?id=276
b=intercept of vegetation line
a=soil line slope
:return: index
"""
return (self.nir - b) / (a * self.red)
def IPVI(self):
"""
Infraself.red percentage vegetation index
https://www.indexdatabase.de/db/i-single.php?id=35
:return: index
"""
return (self.nir / ((self.nir + self.red) / 2)) * (self.NDVI() + 1)
def I(self):
"""
Intensity
https://www.indexdatabase.de/db/i-single.php?id=36
:return: index
"""
return (self.red + self.green + self.blue) / 30.5
def RVI(self):
"""
Ratio-Vegetation-Index
http://www.seos-project.eu/modules/remotesensing/remotesensing-c03-s01-p01.html
:return: index
"""
return self.nir / self.red
def MRVI(self):
"""
Modified Normalized Difference Vegetation Index RVI
https://www.indexdatabase.de/db/i-single.php?id=275
:return: index
"""
return (self.RVI() - 1) / (self.RVI() + 1)
def MSAVI(self):
"""
Modified Soil Adjusted Vegetation Index
https://www.indexdatabase.de/db/i-single.php?id=44
:return: index
"""
return (
(2 * self.nir + 1)
- ((2 * self.nir + 1) ** 2 - 8 * (self.nir - self.red)) ** (1 / 2)
) / 2
def NormG(self):
"""
Norm G
https://www.indexdatabase.de/db/i-single.php?id=50
:return: index
"""
return self.green / (self.nir + self.red + self.green)
def NormNIR(self):
"""
Norm self.nir
https://www.indexdatabase.de/db/i-single.php?id=51
:return: index
"""
return self.nir / (self.nir + self.red + self.green)
def NormR(self):
"""
Norm R
https://www.indexdatabase.de/db/i-single.php?id=52
:return: index
"""
return self.red / (self.nir + self.red + self.green)
def NGRDI(self):
"""
Normalized Difference self.green/self.red Normalized self.green self.red
difference index, Visible Atmospherically Resistant Indices self.green (VIself.green)
https://www.indexdatabase.de/db/i-single.php?id=390
:return: index
"""
return (self.green - self.red) / (self.green + self.red)
def RI(self):
"""
Normalized Difference self.red/self.green self.redness Index
https://www.indexdatabase.de/db/i-single.php?id=74
:return: index
"""
return (self.red - self.green) / (self.red + self.green)
def S(self):
"""
Saturation
https://www.indexdatabase.de/db/i-single.php?id=77
:return: index
"""
max = np.max([np.max(self.red), np.max(self.green), np.max(self.blue)])
min = np.min([np.min(self.red), np.min(self.green), np.min(self.blue)])
return (max - min) / max
def IF(self):
"""
Shape Index
https://www.indexdatabase.de/db/i-single.php?id=79
:return: index
"""
return (2 * self.red - self.green - self.blue) / (self.green - self.blue)
def DVI(self):
"""
Simple Ratio self.nir/self.red Difference Vegetation Index, Vegetation Index
Number (VIN)
https://www.indexdatabase.de/db/i-single.php?id=12
:return: index
"""
return self.nir / self.red
def TVI(self):
"""
Transformed Vegetation Index
https://www.indexdatabase.de/db/i-single.php?id=98
:return: index
"""
return (self.NDVI() + 0.5) ** (1 / 2)
def NDRE(self):
return (self.nir - self.redEdge) / (self.nir + self.redEdge)
"""
# genering a random matrices to test this class
red = np.ones((1000,1000, 1),dtype="float64") * 46787
green = np.ones((1000,1000, 1),dtype="float64") * 23487
blue = np.ones((1000,1000, 1),dtype="float64") * 14578
redEdge = np.ones((1000,1000, 1),dtype="float64") * 51045
nir = np.ones((1000,1000, 1),dtype="float64") * 52200
# Examples of how to use the class
# instantiating the class
cl = IndexCalculation()
# instantiating the class with the values
#cl = indexCalculation(red=red, green=green, blue=blue, redEdge=redEdge, nir=nir)
Create codespell.yml (#1698) * fixup! Format Python code with psf/black push * Create codespell.yml * fixup! Format Python code with psf/black push
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# how set the values after instantiate the class cl, (for update the data or when don't
add the index calculation class at digital_image_processing and the hamming code algorithm at hashes (#1152) * add the index calculation at difital_image_processing file * make changes at index_calculation * update the variables to self variables at functions * update the word wrap in comments at index_calculation * add the hamming code algorithm * Wrap long lines
2019-12-06 06:13:10 +00:00
# instantiating the class with the values)
cl.setMatrices(red=red, green=green, blue=blue, redEdge=redEdge, nir=nir)
# calculating the indices for the instantiated values in the class
# Note: the CCCI index can be changed to any index implemented in the class.
indexValue_form1 = cl.calculation("CCCI", red=red, green=green, blue=blue,
redEdge=redEdge, nir=nir).astype(np.float64)
indexValue_form2 = cl.CCCI()
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# calculating the index with the values directly -- you can set just the values
# preferred note: the *calculation* function performs the function *setMatrices*
add the index calculation class at digital_image_processing and the hamming code algorithm at hashes (#1152) * add the index calculation at difital_image_processing file * make changes at index_calculation * update the variables to self variables at functions * update the word wrap in comments at index_calculation * add the hamming code algorithm * Wrap long lines
2019-12-06 06:13:10 +00:00
indexValue_form3 = cl.calculation("CCCI", red=red, green=green, blue=blue,
redEdge=redEdge, nir=nir).astype(np.float64)
print("Form 1: "+np.array2string(indexValue_form1, precision=20, separator=', ', floatmode='maxprec_equal'))
print("Form 2: "+np.array2string(indexValue_form2, precision=20, separator=', ', floatmode='maxprec_equal'))
print("Form 3: "+np.array2string(indexValue_form3, precision=20, separator=', ', floatmode='maxprec_equal'))
# A list of examples results for different type of data at NDVI
# float16 -> 0.31567383 #NDVI (red = 50, nir = 100)
# float32 -> 0.31578946 #NDVI (red = 50, nir = 100)
# float64 -> 0.3157894736842105 #NDVI (red = 50, nir = 100)
# longdouble -> 0.3157894736842105 #NDVI (red = 50, nir = 100)
"""
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