code: def _star_kernel(m, n):
      c = m + m // 2 - n - n // 2
      outer_star = star(m)
      inner_star = np.zeros_like(outer_star)
      inner_star[c:-c, c:-c] = star(n)
      outer_weight = 1.0 / (np.sum(outer_star - inner_star))
      inner_weight = 1.0 / np.sum(inner_star)
      bfilter = (
          outer_weight * outer_star
          - (outer_weight + inner_weight) * inner_star
      )
      return bfilter
  
file_path: scikit-image/skimage/feature/censure.py
imports: import numpy
  from scipy.ndimage import maximum_filter, minimum_filter, convolve
  from ..transform import integral_image
  from .corner import structure_tensor
  from ..morphology import octagon, star
  from .censure_cy import _censure_dob_loop
  from ..feature.util import FeatureDetector, _prepare_grayscale_input_2D, _mask_border_keypoints
  from .._shared.utils import check_nD
label_desc: Use image node_id 3 for calling a global function with example usage: _star_kernel(m, n) and returns: bfilter