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Author SHA1 Message Date
Max Sponsel
12dd773020 Korrektur des Algorithmus
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.
2020-07-11 09:40:29 +02:00
Max Sponsel
871715bbad Merge remote-tracking branch 'origin/master' 2020-07-09 16:06:51 +02:00
Max Sponsel
1165dc1e21 Fehler im Algorithmus gefunden
Anders als im Paper werden die RGB Werte nicht in der Reihenfolge Rot Grün Blau (RGB), sondern in OpenCV als Blau grün rot (BGR) abgespeichert.
Also ist ein e Funktion zum "Umdrehen" der Matrix nötig!
2020-07-09 16:06:27 +02:00
2 changed files with 11 additions and 11 deletions

19
.idea/workspace.xml generated
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@ -66,6 +66,7 @@
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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')