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Asked: 2026-05-11T05:47:55+00:00

I’m trying to add two images together using NumPy and PIL. The way I

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I’m trying to add two images together using NumPy and PIL. The way I would do this in MATLAB would be something like:

>> M1 = imread('_1.jpg'); >> M2 = imread('_2.jpg'); >> resM = M1 + M2; >> imwrite(resM, 'res.jpg');

I get something like this:

alt text http://www.deadlink.cc/matlab.jpg

Using a compositing program and adding the images the MATLAB result seems to be right.

In Python I’m trying to do the same thing like this:

from PIL import Image from numpy import *  im1 = Image.open('/Users/rem7/Desktop/_1.jpg') im2 = Image.open('/Users/rem7/Desktop/_2.jpg')  im1arr = asarray(im1) im2arr = asarray(im2)  addition = im1arr + im2arr  resultImage = Image.fromarray(addition) resultImage.save('/Users/rem7/Desktop/a.jpg')

and I get something like this:

alt text http://www.deadlink.cc/python.jpg

Why am I getting all those funky colors? I also tried using ImageMath.eval('a+b', a=im1, b=im2), but I get an error about RGB unsupported.

I also saw that there is an Image.blend() but that requires an alpha.

What’s the best way to achieve what I’m looking for?

Source Images (images have been removed):

alt text http://www.deadlink.cc/_1.jpg alt text http://www.deadlink.cc/_2.jpg

Humm, OK, well I added the source images using the add image icon and they show up when I’m editing the post, but for some reason the images don’t show up in the post.

(images have been removed) 2013 05 09

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1 Answer

  1. As everyone suggested already, the weird colors you’re observing are overflow. And as you point out in the comment of schnaader’s answer you still get overflow if you add your images like this:

    addition=(im1arr+im2arr)/2

    The reason for this overflow is that your NumPy arrays (im1arr im2arr) are of the uint8 type (i.e. 8-bit). This means each element of the array can only hold values up to 255, so when your sum exceeds 255, it loops back around 0:

    >>>array([255,10,100],dtype='uint8') +  array([1,10,160],dtype='uint8') array([ 0, 20,  4], dtype=uint8)

    To avoid overflow, your arrays should be able to contain values beyond 255. You need to convert them to floats for instance, perform the blending operation and convert the result back to uint8:

    im1arrF = im1arr.astype('float') im2arrF = im2arr.astype('float') additionF = (im1arrF+im2arrF)/2 addition = additionF.astype('uint8')

    You should not do this:

    addition = im1arr/2 + im2arr/2

    as you lose information, by squashing the dynamic of the image (you effectively make the images 7-bit) before you perform the blending information.

    MATLAB note: the reason you don’t see this problem in MATLAB, is probably because MATLAB takes care of the overflow implicitly in one of its functions.

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