Mahotas - RGB to XYZ Conversion

Mahotas - RGB to XYZ Conversion

Mahotas is a computer vision and image processing library for Python. However, as of my last update, Mahotas itself doesn't directly provide a function for converting an RGB image to XYZ color space. RGB to XYZ conversion is a color space transformation that can be performed using matrix multiplication with a specific conversion matrix.

While you can certainly implement this conversion manually, it might be easier and more efficient to use a library like OpenCV or scikit-image, which already have built-in functions for various color space conversions.

If you want to do it manually or using Mahotas for some operations, here's a basic implementation of RGB to XYZ conversion:

Manual Implementation of RGB to XYZ Conversion

The transformation from RGB to XYZ color space can be done using a linear transformation. The RGB values should first be normalized to the range 0-1.

Here's a simple Python function to perform this conversion:

import numpy as np def rgb_to_xyz(rgb_image): # Normalize the RGB values to the 0-1 range normalized_rgb = rgb_image / 255.0 # Conversion matrix matrix = np.array([[0.412453, 0.357580, 0.180423], [0.212671, 0.715160, 0.072169], [0.019334, 0.119193, 0.950227]]) # Apply the matrix transformation xyz_image = np.dot(normalized_rgb, matrix.T) # Clip values to 0-1 range if necessary xyz_image = np.clip(xyz_image, 0, 1) return xyz_image # Example usage with a dummy RGB image rgb_image = np.random.randint(0, 256, (100, 100, 3), dtype=np.uint8) xyz_image = rgb_to_xyz(rgb_image)

In this function:

  • rgb_image is assumed to be a NumPy array with shape (height, width, 3) where the last dimension represents the R, G, and B channels.
  • The conversion matrix used is a standard one for converting sRGB (standard RGB) to XYZ.
  • The RGB image is first normalized to the range 0-1 because the matrix is designed for this range.
  • After the matrix multiplication, the result is in the XYZ color space.

Using Other Libraries

If you have access to OpenCV, you can use it for color space conversions:

import cv2 # Assuming rgb_image is your input image xyz_image = cv2.cvtColor(rgb_image, cv2.COLOR_RGB2XYZ)

Or, if you're using scikit-image:

from skimage import color # Assuming rgb_image is your input image xyz_image = color.rgb2xyz(rgb_image)

These libraries are optimized for image processing tasks and support a wide range of color space conversions, including RGB to XYZ.

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