Moore-Penrose Inverse¶

Computes the Moore-Penrose Inverse Matrix, an important step in computing the homography for color correction.

plantcv.transform.get_matrix_m(target_matrix, source_matrix)

returns matrix_a, matrix_m, matrix_b

• Parameters

  • target_matrix = a n x 4 matrix containing the average red value, average green value, and average blue value for each color chip.
  • source_matrix = a n x 4 matrix containing the average red value, average green value, and average blue value for each color chip.

• Returns

  • matrix_a = a concatenated n x 9 matrix of source_matrix red, green, and blue values to the powers 1, 2, 3
  • matrix_m = a 9 x n Moore-Penrose inverse matrix
  • matrix_b = a n x 9 matrix of linear, quadratic, and cubic RGB values from target_img

from plantcv import plantcv as pcv

matrix_a, matrix_m, matrix_b = pcv.transform.get_matrix_m(target_matrix, source_matrix)

print("Moore-Penrose Inverse Matrix: ")
print(matrix_m)