Add (bi-)cubic interpolation

skimage/transform/_geometric.py

@@ -834,7 +834,7 @@ def warp(image, inverse_map=None, map_args={}, output_shape=None, order=1,
 
     # use fast Cython version for specific parameters
     fast_modes = ('constant', 'reflect', 'wrap')
-    if order in (0, 1) and mode in fast_modes and not map_args:
+    if order in (0, 1, 3) and mode in fast_modes and not map_args:
         matrix = None
         if isinstance(inverse_map, HOMOGRAPHY_TRANSFORMS):
             matrix = inverse_map._matrix

skimage/transform/_warps_cy.pyx

@@ -5,8 +5,9 @@
 
 cimport numpy as np
 import numpy as np
-from skimage._shared.interpolation cimport (nearest_neighbour,
-                                            bilinear_interpolation)
+from skimage._shared.interpolation cimport (nearest_neighbour_interpolation,
+                                            bilinear_interpolation,
+                                            bicubic_interpolation)
 
 
 cdef inline void _matrix_transform(double x, double y, double* H, double *x_,
@@ -108,9 +109,11 @@ def _warp_fast(np.ndarray image, np.ndarray H, output_shape=None, int order=1,
     cdef double (*interp_func)(double*, int, int, double, double,
                                char, double)
     if order == 0:
-        interp_func = nearest_neighbour
+        interp_func = nearest_neighbour_interpolation
     elif order == 1:
         interp_func = bilinear_interpolation
+    elif order == 3:
+        interp_func = bicubic_interpolation
 
     for tfr in range(out_r):
         for tfc in range(out_c):

skimage/transform/tests/test_warps.py

@@ -57,7 +57,7 @@ def test_fast_homography():
     tform = ProjectiveTransform(H)
     coords = warp_coords(tform.inverse, (img.shape[0], img.shape[1]))
 
-    for order in range(2):
+    for order in range(4):
         for mode in ('constant', 'reflect', 'wrap'):
             p0 = map_coordinates(img, coords, mode=mode, order=order)
             p1 = warp(img, tform, mode=mode, order=order)