diff --git a/Code/Dyschromasie.py b/Code/Dyschromasie.py
index 05bd2ae..4c47eae 100644
--- a/Code/Dyschromasie.py
+++ b/Code/Dyschromasie.py
@@ -5,7 +5,7 @@ import sys
 
 # Einlesen des Bildes
 script_dir = sys.path[0]
-path = script_dir[:-4] + "Beispielbilder\lena.jpg"
+path = script_dir[:-4] + "Beispielbilder\grocery_store.jpg"
 image = cv2.imread(path)  # Einlesen des Bildes (noch hardcodiert, sollte dann in GUI gehen)
 
 rows = image.shape[0]  # Auslesen der Zeilenanzahl
@@ -64,7 +64,7 @@ T_reversed = np.array([[5.47221206, -4.6419601, 0.16963708],
 
 # Simulationsmatrizen fuer Protanop
 
-S_b = np.array([[0, 1.05118294, -0.05116099],  #Simulationsmatrix fuer Protanopie
+S_p = np.array([[0, 1.05118294, -0.05116099],  #Simulationsmatrix fuer Protanopie
                 [0, 1, 0],
                 [0, 0, 1]])
 
@@ -80,7 +80,7 @@ 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_b.dot(T.dot(cb_image[i, j]))) #T^-1*S*T*RBG_values
+        cb_image[i,j]  = T_reversed.dot(S_p).dot(T).dot(cb_image[i,j])
 
 sim_image = np.copy(cb_image)
 sim_image = sim_image.astype('uint8')
@@ -89,7 +89,7 @@ sim_image = sim_image.astype('uint8')
 for i in range(rows):
     for j in range(cols):
         for x in range(3):
-            sim_image[i, j, x] = int(reverseGammaCorrection(cb_image[i, j, x]))
+            sim_image[i, j, x] = reverseGammaCorrection(cb_image[i, j, x])
 
 
 cv2.namedWindow("Display")  # Displaywindow erstellen