SponselMa71420/Projekt_Dyschromasie
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Korrektur des Algorithmus

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Durch die NumPy Funktion numpy.flipud konnte das RGB Array umgedreht, der Algorithmus des Papers angewendet und schließlich eine Rücktransformation der RGB Werte stattfinden. Die erhaltenen Bilder entsprechen nun den Erwartungen.
This commit is contained in:
Max Sponsel 2020-07-11 09:40:29 +02:00
parent 871715bbad
commit 12dd773020
2 changed files with 11 additions and 11 deletions
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19
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Code/Dyschromasie.py
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@ -32,7 +32,6 @@ def reverseGammaCorrection(v_reverse):
print("Ungültiger Wert!!!") print("Ungültiger Wert!!!")
return 1 return 1
cb_image = np.copy(image) # Kopie des Bildarrays cb_image = np.copy(image) # Kopie des Bildarrays
cb_image = cb_image.astype('float64') # Casting des Arrays auf Float cb_image = cb_image.astype('float64') # Casting des Arrays auf Float
@ -78,7 +77,7 @@ S_t = np.array([[1, 0, 0], #Simulationsmatrix fuer Tritanopi
#Multiplikation der einzelnen Pixel #Multiplikation der einzelnen Pixel
for i in range(rows): for i in range(rows):
for j in range(cols): for j in range(cols):
cb_image[i,j] = T_reversed.dot(S_p).dot(T).dot(cb_image[i,j]) #ToDo Statt RBG ist noch BGR cb_image[i,j] = np.flipud(T_reversed.dot(S_p).dot(T).dot(np.flipud(cb_image[i,j]))) #ToDo Statt RBG ist noch BGR
sim_image = np.copy(cb_image) sim_image = np.copy(cb_image)
sim_image = sim_image.astype('uint8') sim_image = sim_image.astype('uint8')