I want to change the color basis of an image from RGB to something else. I have a matrix M that I want to apply to each pixel's RGB, which we can define as xij.
I am currently iterating over each pixel of the NumPy image and calculating Mxij manually. I can't even vectorize it over the rows, because the RGB is a 1x3 instead of a 3x1 array.
Is there a better way to do this? Maybe a function in OpenCV or NumPy?
Can't remember the canonical way to do this (possibly avoiding the transposes) but this should work:
import numpy as np M = np.random.random_sample((3, 3)) rgb = np.random.random_sample((5, 4, 3)) slow_result = np.zeros_like(rgb) for i in range(rgb.shape[0]): for j in range(rgb.shape[1]): slow_result[i, j, :] = np.dot(M, rgb[i, j, :]) # faster method rgb_reshaped = rgb.reshape((rgb.shape[0] * rgb.shape[1], rgb.shape[2])) result = np.dot(M, rgb_reshaped.T).T.reshape(rgb.shape) print np.allclose(slow_result, result) If it's a transformation between standard colorspaces then you should use Scikit Image:
