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.
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Max Sponsel committed 2020-07-11 09:40:29 +02:00
1 parent 871715bbad
commit 12dd773020
2 files changed
+11 -11
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.idea/workspace.xml
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+10 -9
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@@ -66,6 +66,7 @@
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Code/Dyschromasie.py
+1 -2
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@@ -32,7 +32,6 @@ def reverseGammaCorrection(v_reverse):
print("Ungültiger Wert!!!")
return 1
cb_image = np.copy(image) # Kopie des Bildarrays
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
for i in range(rows):
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 = sim_image.astype('uint8')