White balance is important for most single-camera NDVI systems, but could be irrelevant to dual-camera systems. The goal is to capture photos with values in the visible and NIR channels that allow computation of meaningful NDVI values. So for pixels of healthy plants, values in the NIR channel must be several times higher than the values in the visible channel.
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The relative brightness of the VIS and NIR channels in a single-camera system can be modified by doing a custom white balance, but this is a bit of a kludge. In dual-camera systems the relative brightness of the VIS and NIR channels can be modified by adjusting the exposure setting of one or both cameras. If the NIR values are not high enough for meaningful NDVI, the exposure of the NIR camera can be changed to make the values higher (brighter). Your calibration targets can be used to do this objectively so that your NDVI results are calibrated. Because you are capturing RAW images, you can adjust the exposure (by a stop or two) during post processing so that your targets are the proper brightness. Then the computed NDVI values should be correct. When the NIR and VIS channels are properly adjusted (calibrated), you can combine them into a single image, although there may be no reason to do that. NDVI or other indices can be calculated from two separate images. False color IR images can also be produced from two separate images. A single four band image might be a nice way to store the data.

Chris

This is again a reason why you would want to know the spectral response of most imaging sensors. Without this information it will require field validation if you want to infer any quantitative data from these NDVI values.

Or without knowing the spectral response of the sensor, you can brute force the response of a dual-camera system by shooting through narrow band pass filters to capture only the bands you want to use for NDVI. The wavelengths used for both NIR and VIS could then be similar to those used in legacy NDVI. If you use calibration targets to calibrate the relative intensity of NIR vs VIS, those results could be comparable with legacy NDVI. Narrow band pass filters require longer exposure times so are not so suitable for UAV or kite use, but are easy to use on tripod mounted systems.

Good point, I might use this approach to see if I can get better results on my PRI sensor. Things were funky and this offset in response (difference in transmission of the filters + spectral response) is probably the cause and something I need to address. I'm still working on the full spectral response of the raspberry pi but for now this has taken a back seat.