You can read the original ITU-R Recommendation 709 6th edition. The value of each grayscale pixel is calculated as the. L = R * 2125/10000 + G * 7154/10000 + B * 0721/10000 This example converts an image with RGB channels into an image with a single grayscale channel. You can read the original ITU-R Recommendation 601 7th edition. help() Help on function grayscale in module PIL.ImageOps: grayscale(image) Convert the image to grayscale. L = R * 299/1000 + G * 587/1000 + B * 114/1000īy iterating through each pixel you can convert 24-bit to 8-bit or 3 channel to 1 channel for each pixel by using the formula above. ITU-R 601 7th Edition Construction of Luminance formula: One of the standards that can be used is Recommendation 601 from ITU-R (Radiocommunication Sector of International Telecommunication Union or ITU) organization which is also used by pillow library while converting color images to grayscale. So, how do we achieve one value from those three pixel values? We need some kind of averaging. If mid is specified, it uses three-color. This function calculates a color wedge which maps all black pixels in the source image to the first color and all white pixels to the second color. L mode on the other hand only uses one value between 0-255 for each pixel (8-bit). Convert Image to RGB and Grayscale using PIL Apby Pupli im Image.open('audacious.png') rgbim im.convert('RGB') rgbim.save('audacious.jpg') from PIL import Image img Image.open('image.png').convert('LA') img.save('greyscale.png') LA mode has luminosity (brightness) and alpha. colorize (image, black, white, mid None, blackpoint 0, whitepoint 255, midpoint 127) source Colorize grayscale image. In summary, color images usually use the RGB format which means every pixel is represented by a tuple of three value (red, green and blue) in Python. There are different image hashes that can be used to transform color images to grayscale.
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