fix 8bit-16bit discepencies

skimage/rank/_crank16.pyx

@@ -35,7 +35,7 @@ cdef inline np.uint16_t kernel_autolevel(int* histo, float pop, np.uint16_t g,in
                 break
     delta = imax-imin
     if delta>0:
-        return <np.uint16_t>(maxbin*1.*(g-imin)/delta)
+        return <np.uint16_t>(1.*(maxbin-1)*(g-imin)/delta)
     else:
         return <np.uint16_t>(imax-imin)
 
@@ -59,7 +59,7 @@ cdef inline np.uint16_t kernel_equalize(int* histo, float pop, np.uint16_t g,int
             if i>=g:
                 break
 
-        return <np.uint16_t>((maxbin*1.*sum)/pop)
+        return <np.uint16_t>(((maxbin-1)*sum)/pop)
     else:
         return <np.uint16_t>(0)
 
@@ -107,7 +107,7 @@ cdef inline np.uint16_t kernel_meansubstraction(int* histo, float pop, np.uint16
     if pop:
         for i in range(maxbin):
             mean += histo[i]*i
-        return <np.uint16_t>((g-mean/pop)/2.+midbin)
+        return <np.uint16_t>((g-mean/pop)/2.+(midbin-1))
     else:
         return <np.uint16_t>(0)
 

skimage/rank/tests/test_suite.py

@@ -108,19 +108,16 @@ class TestSequenceFunctions(unittest.TestCase):
         # filters applied on 8bit image ore 16bit image (having only real 8bit of dynamic) should be identical
         i8 = data.camera()
         i16 = i8.astype(np.uint16)
+        assert (i8==i16).all()
+
         methods = ['autolevel','bottomhat','equalize','gradient','maximum','mean'
             ,'meansubstraction','median','minimum','modal','morph_contr_enh','pop','threshold', 'tophat']
+
         for method in methods:
             func = eval('rank.%s'%method)
-            print func
             f8 = func(i8,disk(3))
             f16 = func(i16,disk(3))
-#            if (f8==f16).all() is False:
-            if not (f8==f16).all():
-                
-                print f8
-                print f16
-
+            assert (f8==f16).all()
 
 
 if __name__ == '__main__':