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.

.idea/workspace.xml

@@ -66,6 +66,7 @@
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       <workItem from="1593693652245" duration="183000" />
       <workItem from="1593852460532" duration="308000" />
+      <workItem from="1594452919558" duration="180000" />
     </task>
     <servers />
   </component>
@@ -77,28 +78,28 @@
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   <component name="com.intellij.coverage.CoverageDataManagerImpl">
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+    <SUITE FILE_PATH="coverage/Projekt_Dyschromasie$Dyschromasie.coverage" NAME="Dyschromasie Coverage Results" MODIFIED="1594453055671" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/Code" />
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 </project>

Code/Dyschromasie.py

@@ -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')