Question

I am a python beginner and I am trying to average two NumPy 2D arrays with shape of (1024,1024). Doing it like this is quite fast:

newImage = (image1 + image2) / 2

But now the images have a “mask” that invalidate certain elements if set to zero. That means if one of the elements is zero, the resulting element should also be zero. My trivial solution is:

newImage = numpy.zeros( (1024,1024) , dtype=numpy.int16 )

for y in xrange(newImage.shape[0]):
   for x in xrange(newImage.shape[1]):
      val1 = image1[y][x]  
      val2 = image2[y][x]                            
      if val1!=0 and val2!=0:               
         newImage[y][x] = (val1 + val2) / 2

But this is really slow. I did not time it, but it seems to be slower by a factor of 100.

I also tried using a lambda operator and “map”, but this does not return a NumPy array.

Answer 1

Try this:

newImage = numpy.where(np.logical_and(image1, image2), (image1 + image2) / 2, 0)

Where none of image1 and image2 equals zero, take their mean, otherwise zero.