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Global constant defined for distance cutoff

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emmanuelle
2015-01-29 21:36:08 +01:00
parent 4697d66c85
commit 112b0b4fcd
1 changed files with 6 additions and 5 deletions
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skimage/restoration/_nl_means_denoising.pyx
+6 -5
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@@ -6,6 +6,7 @@ from libc.math cimport exp
ctypedef np.float32_t DTYPE_t
cdef float DISTANCE_CUTOFF = 5.
@cython.boundscheck(False)
cdef inline float patch_distance_2d(DTYPE_t [:, :] p1,
@@ -46,7 +47,7 @@ cdef inline float patch_distance_2d(DTYPE_t [:, :] p1,
cdef float distance = 0
for i in range(s):
# exp of large negative numbers will be 0, so we'd better stop
if distance > 5:
if distance > DISTANCE_CUTOFF:
return 0.
for j in range(s):
tmp_diff = p1[i, j] - p2[i, j]
@@ -91,7 +92,7 @@ cdef inline float patch_distance_2drgb(DTYPE_t [:, :, :] p1,
cdef float distance = 0
for i in range(s):
# exp of large negative numbers will be 0, so we'd better stop
if distance > 5:
if distance > DISTANCE_CUTOFF:
return 0.
for j in range(s):
for color in range(3):
@@ -135,7 +136,7 @@ cdef inline float patch_distance_3d(DTYPE_t [:, :, :] p1,
cdef float tmp_diff
for i in range(s):
# exp of large negative numbers will be 0, so we'd better stop
if distance > 5:
if distance > DISTANCE_CUTOFF:
return 0.
for j in range(s):
for k in range(s):
@@ -431,7 +432,7 @@ def _fast_nl_means_denoising_2d(image, int s=7, int d=13, float h=0.1):
distance = _integral_to_distance_2d(integral, x_row, x_col,
offset, h2s2)
# exp of large negative numbers is close to zero
if distance > 5:
if distance > DISTANCE_CUTOFF:
continue
weight = alpha * exp(- distance)
weights[x_row, x_col] += weight
@@ -543,7 +544,7 @@ def _fast_nl_means_denoising_3d(image, int s=5, int d=7, float h=0.1):
x_pln, x_row, x_col, offset,
s_cube_h_square)
# exp of large negative numbers is close to zero
if distance > 5.:
if distance > DISTANCE_CUTOFF:
continue
weight = alpha * exp(- distance)
weights[x_pln, x_row, x_col] += weight