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copied!<p>As everyone suggested already, the weird colors you're observing are overflow. And as you point out in the <a href="https://stackoverflow.com/questions/524930/numpy-pil-adding-an-image/524943#524943">comment of schnaader's answer</a> you <strong>still get overflow</strong> if you add your images like this:</p> <pre><code>addition=(im1arr+im2arr)/2 </code></pre> <p>The reason for this overflow is that your NumPy arrays (<em>im1arr</em> <em>im2arr</em>) are of the <strong>uint8</strong> 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:</p> <pre><code>>>>array([255,10,100],dtype='uint8') + array([1,10,160],dtype='uint8') array([ 0, 20, 4], dtype=uint8) </code></pre> <p>To avoid overflow, your arrays should be able to contain values beyond 255. You need to <strong>convert them to floats</strong> for instance, perform the blending operation and <strong>convert the result back to uint8</strong>:</p> <pre><code>im1arrF = im1arr.astype('float') im2arrF = im2arr.astype('float') additionF = (im1arrF+im2arrF)/2 addition = additionF.astype('uint8') </code></pre> <p>You <strong>should not</strong> do this:</p> <pre><code>addition = im1arr/2 + im2arr/2 </code></pre> <p>as you lose information, by squashing the dynamic of the image (you effectively make the images 7-bit) before you perform the blending information.</p> <p><strong>MATLAB note</strong>: 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.</p>

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