Code/Dyschromasie.py

@@ -14,42 +14,33 @@ kanaele = image.shape[2]  # Auslesen der Kanaele (3 fuer RGB, 1 fuer Graubild)
 
 
 def gammaCorrection(v):
-    if v <= 0.04045 * 255:
-        return float(((v / 255) / 12.92))
-    elif v > 0.04045 * 255:
-        return float((((v / 255) + 0.055) / 1.055) ** 2.4)
+    if (v <= 0.04045 * 255):
+        return ((v / 255) / 12.92)
+    elif (v > 0.04045 * 255):
+        return (((v / 255) + 0.055) / 1.055) ** 2.4
     else:
         print("Ungültiger Wert!!")
         return 1
 
+
 def reverseGammaCorrection(v_reverse):
-    if v_reverse <= 0.0031308:
-        return int(255 * (12.92 * v_reverse))
-    elif v_reverse > 0.0031308:
-        return int(255 * (1.055 * v_reverse ** 0.41666 - 0.055))
+    if (v_reverse <= 0.0031308):
+        return 255 * (12.92 * v_reverse)
+    elif (v_reverse > 0.0031308):
+        return 255 * (1.055 * v_reverse ** 0.41666 - 0.055)
     else:
         print("Ungültiger Wert!!!")
         return 1
 
-
-cb_image = np.copy(image)                   #Kopie des Bildarrays
-cb_image = cb_image.astype('float64')       #Casting des Arrays auf Float
-
-#Korrektur des Gamma Faktors für alle Bildelemente
-for i in range(rows):
-    for j in range(cols):
-        for x in range(3):
-            cb_image[i, j, x] = gammaCorrection(float(image[i, j, x]))
-
 '''
         0.31399022 0.63951294 0.04649755   Transformationsmatrix zum Konvertieren vom linearen RGB zum LMS Farbraum
 T   =   0.15537241 0.75789446 0.08670142   Multiplikation aus Brucelindbloom und Hunt-Pointer-Estevez Matrixen 
         0.01775239 0.10944209 0.87256922   T*RGB_Farbverktor = LMS_Farbvektor
 '''
 
-T = np.array([[0.31399022, 0.63951294, 0.04649755],
-              [0.15537241, 0.75789446, 0.08670142],
-              [0.01775239, 0.10944209, 0.87256922]])
+T = np.array([[0.31399022,0.63951294,0.04649755],
+              [0.15537241,0.75789446,0.08670142],
+              [0.01775239,0.10944209,0.87256922]])
 
 '''
                5.47221206 −4.6419601   0.16963708    Rücktransformationsmatrix (Inverse von T)
@@ -57,12 +48,15 @@ T_reversed  = -1.1252419  2.29317094  −0.1678952     T_reversed Ü LMS_Farbvek
                0.02980165 −0.19318073  1.16364789
 '''
 
-T_reversed = np.array([[5.47221206, -4.6419601, 0.16963708],
-                       [-1.1252419, 2.29317094, -0.1678952],
-                       [0.02980165, -0.19318073, 1.16364789]])
+T_reversed = np.array([[5.47221206,-4.6419601,0.16963708],
+                       [-1.1252419,2.29317094,-0.1678952],
+                       [0.02980165,-0.19318073,1.16364789]])
 
-# Multiplikation der einzelnen Pixelwerte
-# T.dot(image[x][y])
+
+# for i in range(rows):           #Durchgehen aller Pixel des Bildes
+#   for j in range(cols):
+#      k = image[i,j]
+#      #Umwandlungsalgorithmus
 
 
 cv2.namedWindow("Display")  # Displaywindow erstellen