In this context, EV stands for "exposure value": en.wikipedia.org/wiki/Exposure_value
Ghosting in HDR merge occurs when there's movement in objects in the scene between the shots, e.g. foliage. Obviously the frames must be aligned before merging, and HDR software (e.g. Lightroom) does the alignment automatically, but that doesn't help to fix this kind of ghosting.
Capture One seems to eliminate ghosting. My landscape shot was shot on a windy day, and has zero ghosting.
If you're happy with your photos that's fine. No-one is telling you how to do HDR images.
The point being made in this thread is that for those aiming to maximise the quality of the raw data for a HDR scene before merging, ETTR is the way to do it.
I see no point in setting -2EV compensation for highlights in situations where they are not being clipped at 0EV compensation. Applying negative exposure compensation when it isn't necessary just reduces the quality of the raw data.
As Quarkcharmed correctly pointed out, in most cases you need only 2 shots to capture the dynamic range, not 3.
It may depend on your source images and software used. If you can base all your adjustments on raw data and it is linear, then yes, there is no point in underexposing. If any part of image pipeline (starting from sensor readout) makes nonlinear corrections [for highlights], then underexposed images may come handy for restoring better dynamic or color for highlights.
Like when your raw developer software itself cannot perform local tone mapping (or how the HDR image creation process is called), then you may not have full control over linearity of data. For your Adobe products this likely is not the case, but for some other tools it may be.
The data in raw files is almost always linear. HDR merging/blending typically involves applying algorithmic models that 'recover' the original per-pixel illuminance and then converting it back to digital numbers as if it was a single shot. Underexposed shots may or may not add noise depending on the algorithm.
Tone mapping happens after the HDR merge. It happens all the time even without HDR.
One of my favorite links ... nowhere does it say "ev". It does allow "Ev" though.
It's a pity that grammar is going downhill fast as more and more people type with their thumbs and do not give a mojón about correct capitalization.
now where did i put my bayer cfa nikon d500 ...
If you're that picky about capitalisation, then electron volt is not 'ev' but 'eV'.
Ouch, I stand corrected! 😠
My general comment about grammar still stands.
This is an international forum. Different languages have different grammatical rules for capitalization. For example in German ALL nouns are capitalized. Russian has similar rules as English with an important exception, the names of months and days of the week are NOT capitalized. In fact there are even minor differences between US English and British English when it comes to capitalization. So it is not necessary a problem with poor grammar, but more of one often people are using their second or third language to post to this all English forum.
As far as "eV", when used in physics "eV" is a symbol for a unit of the measure of a physical property used in some (but not all) areas of physics. While eV is a unit of energy used in say particle physics, it is not an SI unit (basic nor derived).
As to grammar, Truman, I was mainly commenting about people typing with their thumbs and not bothering to capitalize for the most part. That is bad grammar in any language.
Correct, in physics we can use only EV in SI system - www.convertunits.com/info/exavolt
EV is also used in transportation - dictionary.cambridge.org/dictionary/english/ev
And huh, there are more, in various casing - www.acronymfinder.com/EV.html 🙃
Wow, never heard of that one!
Thanks.
It was a simple binary typo, probably because I started out with "noise" and then changed it to "SNR", which, of course, is a PITA if you are behind in following a thread and don't notice the catch until 19 days later, and a whole threadstorm snowballs in your absence.
It's a lot easier in the long run to simply qualify the nature of the stacks, so there is no question.
Yes, you can get ruined on either end of the raw histogram, but the highlight end is quite drastic, making every would-be higher value record at the clipping point, whereas, at the black end, there is no actual clipping, as black is an asymptote, not a passable value, and decreasing exposure mainly increases noise, but can still show larger image features when it can no longer show fine ones because of too much noise.
