title: matplotlib imshow plots different if using colormap or RGB array
body: <p>I am having the following problem: I am saving 16-bit tiff images with a microscope and I need to analyze them. I want to do that with numpy and matplotlib, but when I want to do something as simple as plotting the image in green (I will later need to superpose other images), it fails.</p>
  
  <p>Here is an example when I try to plot the image either as a RGB array, or with the default <code>jet</code> colormap.</p>
  
  <pre><code>import numpy as np
  import matplotlib.pyplot as plt
  import cv2
  
  imageName = 'image.tif'
  
  # image as luminance 
  img1 = cv2.imread(imageName,-1)
  
  # image as RGB array
  shape = (img1.shape[0], img1.shape[1], 3)
  img2 = np.zeros(shape,dtype='uint16')
  img2[...,1] += img1
  
  fig = plt.figure(figsize=(20,8))
  ax1 = fig.add_subplot(1,2,1)
  ax2 = fig.add_subplot(1,2,2)
  
  im1 = ax1.imshow(img1,interpolation='none')
  im2 = ax2.imshow(img2,interpolation='none')
  fig.show()
  </code></pre>
  
  <p>Which to me yields the following figure: <img src="https://i.stack.imgur.com/la5K8.png" alt="enter image description here"></p>
  
  <p>I am sorry if the question is too basic, but I have no idea why the right plot is showing this artifacts. I would like to get with the green scale, something like how the figure looks (imageJ also yields somthing similar to the left plot).</p>
  
  <p>Thank you very much for your collaboration.</p>