Factory Calibration
Set the beta IP for easy access.
beta=192.168.1.101
1 Step 1: Check range of the input signal
Set gain with:
ssh root@beta "./set_gain.sh 1
Take an overexposed image and check the levels:
ssh root@beta "./cmv_snap3 -2 -b -r -e 100ms" > snap.raw12
raw2dng snap.raw12 --totally-raw
octave
octave:1> a = read_raw('snap.DNG')
octave:2> prctile(a(:), [0.1 1 50 99 99.9])
Lower numbers should be around 50...300 (certainly not zero). Higher numbers should be around 4000, but not 4095.
Repeat for gains 2, 3, 4.
Put this in startup script:
./set_gain 1
2 Step 2: RCN calibration
Take 64 dark frames at 10ms, gain x1.
for i in `seq 1 64`; do ssh root@beta "./cmv_snap3 -2 -b -r -e 10ms" > dark-x1-10ms-$i.raw12 done
Compute a temporary dark frame for RCN calibration:
raw2dng --swap-lines --calc-darkframe dark-x1-10ms-*.raw12
Upload it to the beta:
mv darkframe-x1.pgm darkframe-rcn.pgm scp darkframe-rcn.pgm root@beta:/root/
Set the RCN values:
ssh root@beta "./rcn_darkframe.py darkframe-rcn.pgm
Put this in startup script:
./rcn_darkframe.py darkframe-rcn.pgm
2.1 Validation
Put the lens cap on the camera, and check the image on the HDMI.
Set the matrix gains to x10 or x20. The fixed components of the row and column noise should be gone. You will still see a lot of dynamic row noise though.
3 Step 3: Dark frame calibration
Take dark frames at various exposure times and gains.
for i in 1 2 3 4; do
for e in `seq 1 100`; do
for g in 1 2 3 4; do
ssh root@beta "./set_gain.sh $g"
ssh root@beta "./cmv_snap3 -2 -b -r -e ${e}ms" > dark-x${g}-${e}ms-$i.raw12
done
done
done
Compute dark frames for each gain:
raw2dng --swap-lines --calc-dcnuframe dark-x1-*.raw12 raw2dng --swap-lines --calc-dcnuframe dark-x2-*.raw12 raw2dng --swap-lines --calc-dcnuframe dark-x3-*.raw12 raw2dng --swap-lines --calc-dcnuframe dark-x4-*.raw12
Save the following files (N=1..4):
darkframe-xN.pgm dcnuframe-xN.pgm
These files should be used in postprocessing. Place them in the directory where you capture raw12 files, so raw2dng will use them.
3.1 Validation
On the same dark frames, or - even better - on a new set of dark frames, run:
raw2dng --swap-lines --check-darkframe dark*.raw12 > dark-check.log
Upload the log.
4 Step 4: Color profiling
Set gain x1.
ssh root@beta "./set_gain.sh 1"
Take a picture of the IT8 chart, correctly exposed.
Edit the coordinates and the raw file name in calib_argyll.sh.
ssh root@beta "./cmv_snap3 -2 -b -r -e 10ms" > it8chart.raw12 ./calib_argyll.sh IT8
Save the following files: - ICC profile (*.icc) - OCIO configuration (copy/paste from terminal) + LUT file (*.spi1d)
4.1 Validation
Render the IT8 chart in Blender, using the OCIO configuration.
Same with the ICC profile (Adobe? RawTherapee? What apps support ICC?)
(todo: detailed steps)
5 Step 5: HDMI dark frames
Record a 1-minute clip with lens cap on.
Average odd and even frames.
(todo: polish and upload the averaging script)
(todo: check if the HDMI dark frames can be computed from regular dark frames)
Results: darkframe-hdmi-A.ppm and darkframe-hdmi-B.ppm.
6 Step 6: HDMI filters for raw recovery
This calibration is for to the recorder, not for the camera. It's for recovering the original raw data from the HDMI, so it has nothing to do with sensor profiling and such.
Record some scene with high detail AND rich colors.
Take a raw12 snapshot in the middle of recording. The HDMI stream will pause for a few seconds.
Upload two frames from the paused clip, together with the raw12 file. This calibration will be hardcoded in hdmi4k.
- batch script to copy all the utilities for the workflow - implement this: https://wiki.apertus.org/index.php/Calibration_files - automate HDMI calibration - remind Herbert to fix the line swapping bug