Super-8 enhancement, progress report

[cpixip]

@dgalland

The idea of doing HDR with variable lighting is interesting (but a bit more complex than just varying the exposure time). What is really its advantage, you still have to let 3 frames pass after a change to get the right one like after a shutter change ?

Well, I started actually out with varying the camera’s exposure setting for the different exposures.
However, at least with the old Broadcom stack, all Raspberry Pi cameras (v1/v2/HQ) needed a too long time to settle to the requested exposure value. (Here (second image in that post) is an example of how long it can take for the exposure to stabilize. This is actually not from a Raspberry Pi camera, but very typical for those as well.)

In the end I switched to just let the camera run continously, without changing any setting at all, switching off as much of the “auto”-functions as possible.

@dgalland

So how many frames in total to make your 5 exposures and what resulting fps?
This leads us to the resolution and modes of the HQ camera.
With my application I can measure a maximum fps (capture in python, video mode, jpeg, without network send or processing), I get the following values:
Mode 3 4056x3040 → 3fps
Mode 3 4056x3040 resized 2028x1520 → 9fps
Mode 2 2028x1520 ->13fps
Mode 1 1920x1080 ->19 fps
Obviously it would be better to use mode 3 the only non binned mode but the fps is really too bad especially if you want to do HDR, the HQ camera is really too slow in full resolution.

Well, I get 10 fps per second raw frame rate, using mode 3. That is actually the maximal frame rate you can achieve in this mode. I am working with a resolution of 2016 x 1512, which is slightly less than the one you quoted. All these images are transfered in the live preview to a Win10 PC, requiring a LAN-bandwidth of 130 Mbit/sec.

The actual capture and transfer of the five different exposures takes about 2.20 to 2.30 sec in total. This is because in capture mode, not all frames delivered by the camera are transfered to the Win10 PC. First, because of the (bad) mechanical design of my scanner, I have to wait 0.55 secs after a frame advance for things to settle down mechanically. Furthermore, because I have not yet synchronized the tunable LED source with the frame capture, I simply wait additional 0.25 secs after switching the illumination amplitude before capturing the next exposure and sending it to the client. This reduces the required LAN-bandwidth to about 25 Mbit/sec.

In principle it would be possible to connect a frame trigger signal from the HQ camera (available on a secondary contact pad) and speed up the scanning process by synching LED and camera switching - so far, I have not bothered to try out this idea.

@dgalland

Auto exposure or not ?
Auto exposure is often criticized by those who think that it destroys the exposure balance of the film. This is true of course for a professional film whose exposure has been carefully worked out. But in an amateur film there are very dark or very light scenes that need to be recovered, and this will not be totally possible in post processing.In this case auto-exposure is very useful, it also allows to limit to three images to do the HDR.

The full capture of the available dynamic range of Kodachrome Super-8 film stock is difficult to achieve with only three exposures - in this case you will indeed need some automatic exposure compensation to get most of the data. And you will need to space the different exposures farther appart than the EV-spacing I am using of about 1 EV to capture highlights and deep shadows. With five exposures, I am able to run the scan with constant settings, no matter what the material throws upon the scanner. One further advantage when using closely spaced exposures is camera noise reduction happening during exposure fusion. Here are some more examples of five exposures used for exposure fusion. Some of them might be really difficult to capture with a three exposure setup and auto exposure.

@dgalland

For your still images, we don’t know how the film is but I think it should be better, are you really sure of your focus ? I think there are some artifacts in the second image and also a sharpening problem on the edges ?

Well, that might be. On the other hand, dirt and the like are imaged quite sharply and are well-defined on the scans. I have uploaded the original prime scan as well as the exposure fusion and the restoration result of the frame depicted above.