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Projekt_Dyschromasie
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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.
master
Max Sponsel 4 years ago
parent
871715bbad
commit
12dd773020
2 changed files with 11 additions and 11 deletions
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  1. 10
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      .idea/workspace.xml
  2. 1
    2
      Code/Dyschromasie.py

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.idea/workspace.xml View File

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Code/Dyschromasie.py View File

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
#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')

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