Update ImageFilter.py

added Scobel Filter for higher noise robustness and better edge detection.

working on nonlinear filters.... coming soon...
...tested with relatively big Images have not given Memory Errors...

use it as follows:

im = Image.fromarray(Iarray).convert("RGBA") # or from file....

im3 = ImageFilter.Sobel().filter(im)

im3.show()

PIL/ImageFilter.py

@@ -16,7 +16,7 @@
 #
 
 import functools
-
+from PIL import _imaging as core
 
 class Filter(object):
     pass
@@ -157,7 +157,8 @@ class GaussianBlur(Filter):
 
 
 class UnsharpMask(Filter):
-    """Unsharp mask filter.
+    """
+    Unsharp mask filter.
 
     See Wikipedia's entry on `digital unsharp masking`_ for an explanation of
     the parameters.
@@ -180,6 +181,22 @@ class UnsharpMask(Filter):
     def filter(self, image):
         return image.unsharp_mask(self.radius, self.percent, self.threshold)
 
+class Sobel(Filter):
+
+    """
+    Using the Scobeloperator to integrate perpendicular towards the direction of the derivative.
+    This is good for getting rid of disturbances.
+    """
+    name = "Scobel"
+
+    def __init__(self, size=3):
+        self.size = size
+
+    def filter(self, image):
+        im1 = image.filter( SOBEL1 )
+        im2 = image.filter( SOBEL2 )
+
+        return image._new(core.blend(im1.im, im2.im, 0.5))
 
 class BLUR(BuiltinFilter):
     name = "Blur"
@@ -273,3 +290,19 @@ class SHARPEN(BuiltinFilter):
         -2, 32, -2,
         -2, -2, -2
         )
+
+class SOBEL1(BuiltinFilter):
+    name = "Sobel_1"
+    filterargs = (3, 3), 1, 255, (
+        -1,  0,  1,
+        -2,  0,  2,
+        -1,  0,  1
+        )
+
+class SOBEL2(BuiltinFilter):
+    name = "Sobel_2"
+    filterargs = (3, 3), 1, 255, (
+        -1, -2, -1,
+         0,  0,  0,
+         1,  2,  1
+        )