Correct getPixelIndexesAround missing one pixel

algorithms/context-adaptive_interpolator.py

@@ -54,27 +54,31 @@ h_wImage = Image.new(MODE, (rImage.size[0], rImage.size[1]))
 h_wImagePixels = h_wImage.load()
 
 # Wiener filter.
-def h_w(h, i, j):
+def h_w(hImage, h, i, j):
     # Equation (7)
-    return h[i, j] * sigma(h, i, j) / (sigma(h, i, j) + sigma_0 ** 2)
+    return h[i, j] * sigma(hImage, h, i, j) / (sigma(hImage, h, i, j) + sigma_0 ** 2)
 
 # Minimum of the considered variances.
-def sigma(h, i, j):
+def sigma(hImage, h, i, j):
     # Equation (9)
-    return sigma_q(h, i, j, Q)
+    return sigma_q(hImage, h, i, j, Q)
 
 def getPixelIndexesAround(i, numberOfPixelsInEachDirection):
-    return range(i - numberOfPixelsInEachDirection, i + numberOfPixelsInEachDirection)
+    return range(i - numberOfPixelsInEachDirection, i + numberOfPixelsInEachDirection + 1)
+
+# Expand image with border pixels.
+def getPixelWithinImage(z, upperBound):
+    return max(min(z, upperBound - 1), 0)
 
 # Local variance obtained by Maximum A Posteriori (MAP).
-def sigma_q(h, i, j, q):
+def sigma_q(hImage, h, i, j, q):
     # Equation (8)
     numberOfPixelsInEachDirection = (q - 1) // 2
     B_q = [(x, z) for x in getPixelIndexesAround(i, numberOfPixelsInEachDirection) for z in getPixelIndexesAround(j, numberOfPixelsInEachDirection)]
-    return max(0, (1 / q ** 2) * sum([h[x, z] ** 2 - sigma_0 ** 2 for (x, z) in B_q]))
+    return max(0, (1 / q ** 2) * sum([h[getPixelWithinImage(x, hImage.size[0]), getPixelWithinImage(z, hImage.size[1])] ** 2 - sigma_0 ** 2 for (x, z) in B_q]))
 
 for i in tqdm(range(rImage.size[0])):
     for j in range(rImage.size[1]):
-        h_wImagePixels[i, j] = round(h_w(r, i, j))
+        h_wImagePixels[i, j] = round(h_w(rImage, r, i, j))
 
 h_wImage.rotate(-90).show()