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EDIT: Code is working now, thanks to Mark and zephyr. zephyr also has two alternate working solutions below. I want to divide blend two images with PIL. I found ImageChops.multiply(image1, image2) but I couldn't find a similar divide(image, image2) function. Divide Blend Mode Explained (I used the first two images here as my test sources.) Is there a built-in divide blend function that I missed (PIL or otherwise)? My test code below runs and is getting close to what I'm looking for. The resulting image output is similar to the divide blend example image here: Divide Blend Mode Explained . Is there a more efficient way to do this divide blend operation (less steps and faster)? At first, I tried using lambda functions in Image.eval and ImageMath.eval to check for black pixels and flip them to white during the division process, but I couldn't get either to produce the correct result. EDIT: Fixed code and shortened thanks to Mark and zephyr. The resulting image output matches the output from zephyr's numpy and scipy solutions below. # PIL Divide Blend test import Image, os, ImageMath imgA = Image.open('01background.jpg') imgA.load() imgB = Image.open('02testgray.jpg') imgB.load() # split RGB images into 3 channels rA, gA, bA = imgA.split() rB, gB, bB = imgB.split() # divide each channel (image1/image2) rTmp = ImageMath.eval("int(a/((float(b)+1)/256))", a=rA, b=rB).convert('L') gTmp = ImageMath.eval("int(a/((float(b)+1)/256))", a=gA, b=gB).convert('L') bTmp = ImageMath.eval("int(a/((float(b)+1)/256))", a=bA, b=bB).convert('L') # merge

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