@cguzikowski , if you want, you can attache a cropped image, so that it's smaller size.
In general, the pixel noise increases as you the pixel gain is increased. Part of Auto Exposure control is controlling exposure time and gain (both of which contribute to the image brightness), but higher gain has higher pixel noise and higher exposure values will result in motion blur.
The Qualcomm ISP has lots of liters, including noise reduction, which are applied when you use the ISP snapshot (even though they have not been tuned for the particular camera, the ISP output may result in better de-noised image). There are several types of filters, for example spatial (such as bilateral filter) and temporal (TNR - temporal noise reduction), and it's usually a combination of both with the filter weights increasing as the gain increases (more noise requires more noise reduction).
Currently, MISP does not have any de-noise filtering, but we are working on adding some. That is why i was discussing with you the ability to process the image offline (from the original bayer source). You could save the full raw image and perform any filtering you need in post processing. This approach is similar to using a RAW image on a fancy camera and then importing that into image processing software on a laptop / desktop, which can perform a lot more filters / effects directly on the raw image (loss-less).
What i suspect is that you are testing in the low-light environment and you are seeing the effects of high gain (high pixel noise). the MISP auto exposure tries to balance exposure and gain and there are a few parameters for that, but in your tests you should see what exposure and gain values the camera is at when you see the noisy image. You can use voxl-portal to control exposure and gain to see what the difference is. I believe the max gain for ov64b is 16x (1600).
I am about to set up your use case again for testing and i will investigate the noise and the original ISP snapshot artifact and we can also compare the image noise from the ISP snapshot and misp snapshot.
Unfortunately the lens for ov64b in the Hadron unit is very small, which reduces the amount of light that gets into the sensor. The sensor is 8+K resolution which means the pixel size is small, so the amount of light that gets to each pixel is small. To compensate for that, we would typically want a larger lens, but it is probably not possible to change the lens in this specific Hadron unit (we have not tried).
If you want to explore offline image processing, you would need:
the original raw bayer (which you can already save)
the gain and exposure used for that frame (i will need to check, i thin we had an option to save the exposure and gain as part of the file name).
then you can have offline processing that is dependent on exposure / gain and apply the filters of your choice.
the only down side is that the raw snapshots are huge, but you can probably zip them up if needed to store a lot of them on voxl2 before offloading.
Alex
