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
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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.
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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=target_matrix, source_matrix=s_matrix)
print("Moore-Penrose Inverse Matrix: ")
print(matrix_m)
Source Code: Here