Thank you Bojan,
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By adjusting the curves, you are changing the starting point (bias) and polynomial factors, used to calculate the display brightness for that particular pixel value on the screen.
For example, your data (original pixel value) could be say 128, but the displayed value will be 255. Or, the original pixel value is 10, the displayed value is 120. For pixel value =5, display value could be 0. (please note the factor value in this example is different for different original pixel value - small original values are amplified more than large values).
The processed picture is saved without the curve polynomial in most cases (DPP can save them, though)
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Appreciate the explanation, that's what I've been striving towards.
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Things are a bit more complicated than this, because the eye response to illumination is logarithmic, not linear.. that is why you will find in literature the term "gamma" and it's associated factor.
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If I put 2 and 2 together, gamma is the log curve that is used by the application to display the image and we adjust that to compensate for what our eye sees and what the camera saw. Correct (at least close?)?
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Signal to noise ratio can't possibly be improved by curve adjustment, however it is possible to offset the noise floor so details are brought up.
The price paid for this offset is increased visibility of digitalisation noise (coarser tone resolution).
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Re: SNR, as radio frequency is one of my specialties, I do understand SNR. Its an easy concept to transfer to imaging. I used the term "artificially" for that reason. Its much the same for digital signal processing in radios (actually it is exactly the same), while you can devise algorithms to pull out bits from the noise based on patterns, you are still restricted by the amount of signal present and the noise floor. Substitute bit error rates with "coarser tone resolution".
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BTW, DPP and DSS operate with 12-16 bits of resolution, not 8 bit (0-255) like you mentioned.
Only the final image (in jpg format) is saved with 8-bit resolution
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My 0-255 reference came from something I had just watched as I have been seeking more detail about what is a histogram and how to read it. They may have simply used the concept of a point and shoot camera that only puts out JPEGs. Interestingly, does that mean that the histogram on a DSLR camera is measuring the full resolution of a RAW file (is that range known?) Does it pick a format to display in, 12 or 16 bit?
So many questions come to mind... more reading and researching...
