code: def combine_images(imgs, register=True):
      
      imgs = np.asarray(imgs, dtype="float")
      if register:
          for i in range(1, imgs.shape[0]):
              ret = register_images(imgs[0, :, :], imgs[i, :, :])
              imgs[i, :, :] = rotate_scale_shift(imgs[i, :, :], *ret[:3], np.nan)
      return np.mean(imgs, 0)
docs: Combine similar images into one to reduce the noise
  
      Parameters
      ----------
      imgs: list of 2d array
          Series of images
      register: Boolean, default False
          True if the images should be register before combination
  
      Returns
      -------
      im: 2d array
          The result image
  
      Notes
      -----
      This is an example of the usage of the library