PixInsight Forum (historical)
PixInsight => General => Off-topic => Topic started by: David Serrano on 2009 August 05 11:53:24
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Folks,
When I shoot in RAW mode, my Canon 40D gives me images with a strong red cast. I assume that's caused by it not applying the white balance to the RAWs. Now, for the astronomical pictures, I guess that it gets resolved in the ColorCalibration step, but I don't think this applies to daytime images, since in these cases we not always have a reliable white reference to give to CC. So, how to proceed then? Can the white balance be extracted somehow from the JPGs (I don't think so)?
Edit: changed "diurnal" to "daytime", thanks Sander ;)
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Ah, diurnal = day time. Had to look that one up :)
I think the best way to determine white balance is to take a picture of a known quantity (ie. a color card) and use that to determine calibration factors that can then be applied to other images provided the camera settings haven't changed.
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Upon loading a RAW image, PixInsight spits some info on its standard output (this is a Unix term), including this promising line:
Daylight multipliers: 2.444244 0.930336 1.163797
Dividing the image by these multipliers (scaling activated, since dividing by 0.9 can potentially yield values greater than 1) doesn't give a good result. Then tried some things off the numbers in Statistics, and got a nice image by subtracting the Minimal values, ie:
$T - Min($T)
The scientific validity of this equation I don't know, but for this image in particular it seemed to fit the bill!
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Hi David
This is a bit late, but I hope it helps anyway :P
What I do with daytime images is follow the same principle from astronomical images: first, take several bias images (8, for example). Then, just take 1 shot of a known gray or white target. You may use a T-shirt, a paper, or a cartuline (I own a neutral middle gray card from the analog days, to set the photometer).
Once in PixInsight, just create the master bias averaging the frames. Now, load the gray target's image. Create a preview covering the inside of the target, and use the image statistics to obtain the median. Write down the values. Now you may create a new PixelMath instance that applies both corrections, bias substraction and color correction as linear scaling.
BTW. I found that with most daytime images a histogram midtones adjustment yields too contrasted images, that are hard to process. A gama function gives better results as a first approximation, and may be incorporated in the same PixelMath expression (of course, we are talking about RAW shots here).
For example (for each channel): (($target-bias)*ColorFactor)^GamaValue
Then, you may apply this instance to the whole set of images with a ImageContainer, and voilá :)
PS: Yes, my current status is MIA (missing in action). jajajajajajajaja