`bilinear`: Bilinear interpolator#

Bilinear interpolator, peak finder, line-profile for images

class BilinearImage#

Bilinear interpolator for images … or any data on a regular grid

__call__()#

Function f((y, x)) where f is a continuous function made from the image and (y,x)=(row, column) is the pixel coordinates in natural C-order

coarse_local_maxi(self, Py_ssize_t x) → Py_ssize_t#

Return the nearest local maximum … without sub-pixel refinement

local_maxi(self, coord)#

Return the nearest local maximum … with sub-pixel refinement

Nearest maximum search:: steepest ascent
Sub-pixel refinement:: Second order Taylor expansion of the function; At the maximum, the first derivative is null delta = x-i = -Inverse[Hessian].gradient if Hessian is singular or |delta|>1: use a center of mass.

map_coordinates(self, coordinates)#

Map coordinates of the array on the image

Parameters:: coordinates – 2-tuple of array of the same size (row_array, column_array)
Returns:: array of values at given coordinates

opp_f(self, coord)#

Function -f((y,x)) for peak finding via minimizer.

Gives large number outside the boundaries to return into the image

profile_line(self, src, dst, int linewidth=1, method=u'mean')#

Return the mean or sum of intensity profile of an image measured along a scan line.

Parameters:

src (2-tuple of numeric scalar) – The start point of the scan line.
dst (2-tuple of numeric scalar) – The end point of the scan line. The destination point is included in the profile, in contrast to standard numpy indexing.
linewidth (int) – Width of the scanline (unit image pixel).
method (str) – ‘mean’ or ‘sum’ depending if we want to compute the mean intensity along the line or the sum.

Returns:

The intensity profile along the scan line. The length of the profile is the ceil of the computed length of the scan line.

Return type:

1d array

Inspired from skimage

bilinear: Bilinear interpolator#