[FFmpeg-user] Lossless compression of 10bit grayscale images (stored as 16bit pngs)

[Tom Vercauteren]

Hello,

Apologies for cross-posting a question I initially posted on stackoverflow (
https://stackoverflow.com/q/69739665/17261462) but having had no response
there I thought this mailing list may be a better place for it.

I am trying to encode 10 bit images losslessly in a video format. The
images are stored as 16 bit png files (but only use 10 bit - currently the
least significant ones) and I have been working with ffmpeg to create and
read back the video files.

My best attempt so far is based on
https://stackoverflow.com/a/66180140/17261462 but as mentioned there, I get
some pixel intensity differences which may be due to rounding when
converting between 10 and 16 bit representation. I tried a few different
means (bit shifting, left bit replication, floating point based scaling)
but haven't yet figured out how to get a trully lossless reconstruction.

Below is a small piece of python code to replicate my issue. I probably am
doing something wrong there so feedback would be appreciated.

```python

import subprocessimport numpy as npimport matplotlib.pyplot as
pltimport tempfileimport imageio
# Create simple image
bitdepth = 10
hbd = int(bitdepth/2)
im0 = np.zeros((1<<hbd,1<<hbd),dtype=np.uint16)
im0[:] = np.arange(0,1<<bitdepth).reshape(im0.shape)print('im0',np.min(im0),np.max(im0),im0.shape,im0.dtype)#
tile it to be at least 64 pix
im0 = np.tile(im0, (2,
2))print('im0',np.min(im0),np.max(im0),im0.shape,im0.dtype)
im0ref = im0# bitshift it or rescale intensities#im0 = (im0<<6)#im0 =
(im0<<6) + (im0>>4)
im0 = np.uint16(np.round(im0 *
np.float64((1<<16)-1)/np.float64((1<<10)-1)))print('im0',np.min(im0),np.max(im0),im0.shape,im0.dtype)
# Save it as png
tmp0 = tempfile.NamedTemporaryFile(suffix='.png',
delete=False)print(f'Using tmp file: {tmp0.name}')
imageio.imwrite(tmp0.name,im0)
# Encode with ffmpeg
tmp1 = tempfile.NamedTemporaryFile(suffix='.mkv', delete=False)# note
that adding the following doesn't seem to impact the results #  + '
-bsf:v hevc_metadata=video_full_range_flag=1' \
mycmd = f'ffmpeg -y -i {tmp0.name}' \
  + ' -c:v libx265 -x265-params lossless=1' \
  + ' -pix_fmt gray10be' \
  + f' {tmp1.name}'print(mycmd)
p = subprocess.run(mycmd.split(), capture_output=True)print(
'stdout:', p.stdout.decode() )print( 'stderr:', p.stderr.decode() )

tmp2 = tempfile.NamedTemporaryFile(suffix='.png', delete=False)
mycmd = f'ffmpeg -y -i {tmp1.name}' \
  + ' -pix_fmt gray16be' \
  + f' {tmp2.name}'print(mycmd)
p = subprocess.run(mycmd.split(), capture_output=True)print(
'stdout:', p.stdout.decode() )print( 'stderr:', p.stderr.decode() )
# Read back with ffmpeg
im1 = imageio.imread(tmp2.name)print('im1',np.min(im1),np.max(im1),im1.shape,im1.dtype)
# Bitshift or scale back
im1pre = im1#im1 = (im1>>6)
im1 = np.uint16(np.round(im1 * np.float64((1<<10)-1)/np.float64((1<<16)-1)))
# check the result
plt.figure()
plt.imshow(im0ref)
plt.colorbar()

plt.figure()
plt.imshow(im1)
plt.colorbar()

plt.figure()
plt.imshow(np.int32(im1)-np.int32(im0ref))
plt.colorbar()
print('err: ',np.linalg.norm((np.float32(im1)-np.float32(im0ref)).ravel()))

plt.show()
```

Many thanks,

Tom