kirkt wrote in post #19465486
Here is a fun little experiment to help visualize WB in terms of per-channel exposure instead of CCT.
I shot a CC target in daylight (late afternoon sun). I shot a reference image as one normally would, slightly underexposed so as not to clip any channels. I fixed this exposure and did not change it throughout the shooting exercise. I then placed filters in front of the lens to simulate different color lighting (yellow, orange, red, magenta).
In my raw converter (Raw Photo Processor) I added exposure to each shot so that the GREEN channel fell in the middle of Zone VI (that is, I equalized exposure across all of the images based on the green channel's exposure) for the CC patch that is used for neutral white balance (see yellow arrow in the attached image). I then took a screenshot of the rendered raw file with a raw histogram of the R, G, and B channels, where no white balance has been applied - the histogram is just for the neutral patch indicated by the yellow arrow in the top image (not the entire image). For each lighting condition, one can observe a couple of things:
1) the amount of exposure adjustment changes to get the GREEN channel to the reference value - this is due to the filter factor of each filter (the amount of green light passed by the filter).
2) the more interesting thing to note is the RELATIVE exposure between channels, and how that changes with the different lighting conditions. With no filter, it is apparent that more green exposure is captured, followed by blue, and then red. This makes sense - there are twice as many green photo sites on a sensor than there are blue or red, and there is more blue light from daylight illumination than there is red.
For a camera to WB these different channel exposures, exposure scaling of each channel is done linearly - like adding exposure compensation on a per-channel basis - to make a target neutral, neutral. In a histogram, the exposure adjustment to each channel will make the R, G, and B channels of the neutral patch all fall on top of each other. So, in the first image, with no filter applied, the blue channel would have to be boosted about one-half of a stop and the red channel a little over a full stop to get the R, G, and B values of the neutral patch exposed identically (i.e., neutral).
The red filter image is very interesting - the RED channel in the histogram is gone! It is clipped to beyond the histogram because the red filter cuts so much green light that the image had to bee boosted 3.7 stops to get the green reference properly adjusted. This image would be impossible to WB in post, and I also tried shooting a WB target and doing a custom WB in camera - no luck.
The magenta filter is also interesting - compared to the no filter, you can see that the magenta filter lifts the blue and red exposure so that the blue exposure equals the green, and the red is about one half a stop below those. This filtration is a trick to use in daylight to help boost the signal-to-noise ratio of the R and B channels when shooting in high-contrast conditions where you will be lifting the shadows a lot (increasing SNR equates to decreasing the noise). This is not so relevant any more with camera sensors getting better and better, but back in my Canon 5D days, this trick helped in certain situations. A more intense magenta filter will decrease the overall exposure (higher filter factor) but bring the blue and red channels closer to green - magenta is the complement of green, so this makes sense.
However, if any filter gets too intense and one or two channels are exposed way differently compared to the others (like in the red example above), then the overall color rendering suffers, even if you can possibly WB the image. The color profile for the camera cannot cope with the extreme transformations required to render the image from the heavily biased raw data.
[/nerd]
Yay!
Kirk
Here is a fun little experiment to help visualize WB in terms of per-channel exposure instead of CCT.
I shot a CC target in daylight (late afternoon sun). I shot a reference image as one normally would, slightly underexposed so as not to clip any channels. I fixed this exposure and did not change it throughout the shooting exercise. I then placed filters in front of the lens to simulate different color lighting (yellow, orange, red, magenta).
In my raw converter (Raw Photo Processor) I added exposure to each shot so that the GREEN channel fell in the middle of Zone VI (that is, I equalized exposure across all of the images based on the green channel's exposure) for the CC patch that is used for neutral white balance (see yellow arrow in the attached image). I then took a screenshot of the rendered raw file with a raw histogram of the R, G, and B channels, where no white balance has been applied - the histogram is just for the neutral patch indicated by the yellow arrow in the top image (not the entire image). For each lighting condition, one can observe a couple of things:
1) the amount of exposure adjustment changes to get the GREEN channel to the reference value - this is due to the filter factor of each filter (the amount of green light passed by the filter).
2) the more interesting thing to note is the RELATIVE exposure between channels, and how that changes with the different lighting conditions. With no filter, it is apparent that more green exposure is captured, followed by blue, and then red. This makes sense - there are twice as many green photo sites on a sensor than there are blue or red, and there is more blue light from daylight illumination than there is red.
For a camera to WB these different channel exposures, exposure scaling of each channel is done linearly - like adding exposure compensation on a per-channel basis - to make a target neutral, neutral. In a histogram, the exposure adjustment to each channel will make the R, G, and B channels of the neutral patch all fall on top of each other. So, in the first image, with no filter applied, the blue channel would have to be boosted about one-half of a stop and the red channel a little over a full stop to get the R, G, and B values of the neutral patch exposed identically (i.e., neutral).
The red filter image is very interesting - the RED channel in the histogram is gone! It is clipped to beyond the histogram because the red filter cuts so much green light that the image had to bee boosted 3.7 stops to get the green reference properly adjusted. This image would be impossible to WB in post, and I also tried shooting a WB target and doing a custom WB in camera - no luck.
The magenta filter is also interesting - compared to the no filter, you can see that the magenta filter lifts the blue and red exposure so that the blue exposure equals the green, and the red is about one half a stop below those. This filtration is a trick to use in daylight to help boost the signal-to-noise ratio of the R and B channels when shooting in high-contrast conditions where you will be lifting the shadows a lot (increasing SNR equates to decreasing the noise). This is not so relevant any more with camera sensors getting better and better, but back in my Canon 5D days, this trick helped in certain situations. A more intense magenta filter will decrease the overall exposure (higher filter factor) but bring the blue and red channels closer to green - magenta is the complement of green, so this makes sense.
However, if any filter gets too intense and one or two channels are exposed way differently compared to the others (like in the red example above), then the overall color rendering suffers, even if you can possibly WB the image. The color profile for the camera cannot cope with the extreme transformations required to render the image from the heavily biased raw data.
[/nerd]
Yay!
Kirk
Hosted photo: posted by kirkt in
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forum: RAW, Post Processing & Printing
./showthread.php?p=19465486&i=i10436055
forum: RAW, Post Processing & Printing
You are making some awesome contributions to this thread, Kirk. I’m taking notes!
