Python: Read and write TIFF 16 bit , three channel , colour images

I found an additional alternative to the two methods above.

The scikit-image package can also read 16 bit, three channel TIFF files using both tifffile.py and FreeImage and specifying them as the plugin to be used.

While reading using tifffile.py is probably done more simply in the manner shown by @Jaime, I thought I would show how it is used along with scikit-image in case anyone wants to do it in this manner.

For anyone using Ubuntu, FreeImage is available as libfreeimage3 using apt.

If the tifffile.py plugin option is used the tifffile.py must be copied to the skimage/io/_plugins directory (f.ex. on Ubuntu the full path in my case was /usr/local/lib/python2.7/dist-packages/skimage/io/_plugins/).

>>> import skimage.io
>>> im = skimage.io.imread('a.tif', plugin='tifffile')
>>> im.dtype
dtype('uint16')
>>> im.shape
(288, 384, 3)
>>> im = skimage.io.imread('a.tif', plugin='freeimage')
>>> im.dtype
dtype('uint16')
>>> im.shape
(288, 384, 3)

Writing TIFF files:

>>> skimage.io.imsave('b.tif', im, plugin='tifffile')
>>> skimage.io.imsave('c.tif', im, plugin='freeimage')

Checking the bitdepth of both b.tif and c.tif using ImageMagick shows that each channel in both images are 16 bit.

For me the previous alternatives did not work. I have used gdal successfully for reading a 16bit images of 1 GB.

You can open an image with something like this:

from osgeo import gdal
import numpy as np
ds = gdal.Open("name.tif")
channel = np.array(ds.GetRasterBand(1).ReadAsArray())

There is a list of supported diver that you can use to write the data.

It has limited functionality, especially when it comes to writing back to disk non RGB images, but Christoph Gohlke's tifffile module reads in 3 channel 16-bit TIFFs with no problems, I just tested it:

>>> import tifffile as tiff
>>> a = tiff.imread('Untitled-1.tif')
>>> a.shape
(100L, 100L, 3L)
>>> a.dtype
dtype('uint16')

And Photoshop reads without complaining what I get from doing:

>>> tiff.imsave('new.tiff', a)

The answer by @Jaime works.

In the mean time I managed to also solve the problem using cv2.imread in OpenCV.

By default cv2.imread will convert a 16 bit, three channel image in a.tif to 8 bit as shown in the question.

cv2.imread accepts a flag after the filename ( cv2.imread(filename[, flags]) ) which specifies the colour type of the loaded image cf. the documentation:

1. >0 returns a 3 channel colour image. This results in conversion to 8 bit as shown above.
2. 0 returns a greyscale image. Also results in conversion to 8 bit.
3. <0 returns the image as is. This will return a 16 bit image.

So the following will read the image without conversion:

>>> im = cv2.imread('a.tif', -1)
>>> im.dtype
dtype('uint16')
>>> im.shape
(288, 384, 3)

Note that OpenCV returns the R, G and B channels in reverse order so im[:,:,0] is the B channel, im[:,:,1] the G channel and im[:,:,2] is the R channel.

I have also found that cv2.imwrite can write 16 bit, three channel TIFF files.

>>> cv2.imwrite('out.tif', im)

Checking the bit depth with ImageMagick:

$ identify -verbose out.tif
  Format: TIFF (Tagged Image File Format)
  Class: DirectClass
  Geometry: 384x288+0+0
  Resolution: 72x72
  Print size: 5.33333x4
  Units: PixelsPerInch
  Type: TrueColor
  Base type: TrueColor
  Endianess: MSB
  Colorspace: sRGB
  Depth: 16-bit
  Channel depth:
    red: 16-bit
    green: 16-bit
    blue: 16-bit
  ....