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Filed under: Cameras •Post Production •Production •

RED Highlight Clipping: Solved?

New from RED: how to correct those bothersome clipped highlights I’ve been freaking out about for the last few days. Currently the procedure only seems to work in RED Alert using the DRX slider. This process is intended to work within REDCine using the “highlight” function but at the moment neither Adam Wilt nor I can get it to work (Intel Mac, build 90). That’s being looked into right now.

DRX works to reconstruct highlights in a clipped channel using information from the other channels. It then blends the reconstructed pixels and the original pixels together to create the most natural-looking effect.

When shooting, try not to clip more than one color channel at a time if you can avoid it. One channel isn’t hard to reconstruct. Two make it more difficult. It’s pointed out to me that two channels will rarely clip at the same time, so for part of the image only one channel will be repaired, and in other parts of the image two will be repaired (although the quality may suffer when two channels are clipped).

In RED Alert, open the R3D of the shot in question and look at the histogram. If you’ve got at least one channel that isn’t clipping, you’re in reasonable shape. If you have two channels that aren’t clipping, even better.

Using the exposure slider, back the exposure down until the curves are just touching the right side of the histogram. Then dial in the DRX slider until things look right. Make sure the matrix is turned ON with your desired white balance in place before using DRX, otherwise the algorithm won’t know what white balance you want and won’t know how to reconstruct the channel(s).

That’s it. It’s that easy. The hard part will be keeping an eye on the camera histogram when shooting to protect the quality of the highlights. It’s a strange new world, this land of RAW, and waveform and vectorscopes aren’t the only tools with which we need be familiar. The histogram is our new best friend, as that will be what tells us the quality of the data we are capturing.

A huge “thank you” to Graeme Nattress of RED for his help in solving this issue. I hope we’ll be able to bring you more info on this subject, and others, soon.

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