Image conversion should scale pixel values accordingly

What did you do?

I tried to convert grayscale images of different modes together

What did you expect to happen?

Conversion should scale values; for example, converting from float to 8-bit should have the values scaled by 255, converting from 8-bit to 16-bit should have the values scaled by 65535/255, etc.

What actually happened?

Values are being clamped

>>> img = Image.open('16bit_image.png')
>>> img.mode
'I'
>>> numpy.array(img)
array([[51559, 52726, 50875, ..., 30493, 30991, 29907],
       [51743, 52185, 51221, ..., 30841, 29920, 30793],
       [51279, 50534, 51128, ..., 31532, 30852, 30651],
       ...,
       [28288, 27868, 28032, ..., 34367, 34235, 34312],
       [26900, 27567, 28120, ..., 36229, 34607, 33399],
       [27966, 28224, 27962, ..., 36223, 35851, 34477]], dtype=int32)
>>> numpy.array(img.convert('L'))
array([[255, 255, 255, ..., 255, 255, 255],
       [255, 255, 255, ..., 255, 255, 255],
       [255, 255, 255, ..., 255, 255, 255],
       ...,
       [255, 255, 255, ..., 255, 255, 255],
       [255, 255, 255, ..., 255, 255, 255],
       [255, 255, 255, ..., 255, 255, 255]], dtype=uint8)

Floating point data really doesn't go over well either

>>> img_float = Image.fromarray(numpy.divide(numpy.array(img), 2**16-1))
>>> numpy.array(img_float)
array([[0.7867399 , 0.8045472 , 0.77630275, ..., 0.46529335, 0.47289234,
        0.45635158],
       [0.78954756, 0.79629207, 0.78158236, ..., 0.4706035 , 0.45654994,
        0.46987107],
       [0.78246737, 0.7710994 , 0.7801633 , ..., 0.48114747, 0.47077134,
        0.46770427],
       ...,
       [0.4316472 , 0.42523843, 0.4277409 , ..., 0.5244068 , 0.52239263,
        0.52356756],
       [0.41046768, 0.42064545, 0.4290837 , ..., 0.55281913, 0.52806896,
        0.50963604],
       [0.4267338 , 0.43067065, 0.42667276, ..., 0.5527275 , 0.5470512 ,
        0.5260853 ]], dtype=float32)
>>> img_oct = img_float.convert('L')
>>> numpy.array(img_oct)
array([[0, 0, 0, ..., 0, 0, 0],
       [0, 0, 0, ..., 0, 0, 0],
       [0, 0, 0, ..., 0, 0, 0],
       ...,
       [0, 0, 0, ..., 0, 0, 0],
       [0, 0, 0, ..., 0, 0, 0],
       [0, 0, 0, ..., 0, 0, 0]], dtype=uint8)
>>>

The input image is a 16 bit PNG made with GIMP, as attached below.
terrain_input.png

What versions of Pillow and Python are you using?

Using Python 3.6.5 and Pillow 5.1.0

No source file or test is named. Reproduce the reported conversions from 16-bit and floating-point grayscale images to 'L', then trace Pillow's image-mode conversion entry points; done means values are scaled to the destination range rather than clamped, with coverage for the examples shown.