I want the nitty gritty - WHY is ISO better than brightening in post, if ISO = "analog post"?

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Note: I'm not asking for ISO advice advice like "what should I do to get less noise? what settings should I use?".. I'm past all that. This is just to improve my understanding of how ISO works.

Many articles that claim to tell you how it works, don't... they boil down to "here's what settings you should use" and "here's what happens if you don't". They gloss over how it actually works.

Example: "The reasons for potential decreases in quality when only increasing exposure in post-processing have to do with digital amplification (post-processing) versus analog amplification (changing ISO), but they are beyond the scope of this article."

It seems like post-process brightening cannot be better than brightening with ISO, for some physics reason. At best it can be roughly the same. But why is that?
Maybe the answer lies in this pretty detailed answer, but I think anyone who understands a subject well enough to can give an "ELI5" summary.

When I look at examples of supposedly "isoless" cameras, they still have a very gentle upward curve on photonstophotos.net, indicating they aren't quite isoless, it's still slightly better to shoot with proper ISO. Except one example, I found, the Fuji XT1, which has this odd dip, which then resumes its near-horizontal plot on the graph:
So what can this analog process do, apparently post-capture, that can't be replicated by a digital process?

To forestall some anticipated responses:

• I already know that real light on the sensor is better than boosting iso... whether that's through slower shutter speed, larger aperture, or more external lighting. More signal = less noise.

• I'm aware that increasing ISO isn't actually increasing 'exposure', because the amount of light hitting the sensor doesn't change. So changing ISO alone, without touching shutter speed or aperture, is not an effective way to ETTR.

• My understanding is that ISO happens after the exposure is captured, that the photons create an electric charge, which are fed into some analog-to-digital converter, and now the charge becomes the 1's and 0's needed to make a brightness number (typically 8 or 10 bit).

• I know that some cameras are fairly ISO invariant, so that you can pretty much shoot at base ISO all the time and brighten in post, and it's almost the same as just using ISO during the capture.

That's the part that baffles me: the "almost"

If ISO boils down to an analog way to post-process the shot, why is that analog way always superior to any digital post-process brightening, even by just 1%?
 
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Yes. It's an additional option. But what you're not seeing in this discussion is anything that shows how that option is clearly better, just assertions that it is.
Consider a high DR scene such as a church interior featuring important details and colors in the highlights (e.g., stained glass windows) and in the shadowed and poorly lit areas (e.g., elaborate woodwork, stonework, artwork, etc. or people).
As I wrote, it's an option to tackle a scene differently. But everyone's missing one of my points: is it significantly better to expose at base ISO and "recover" shadows or just use a higher ISO value (taking into account highlights).

There's a reason why I and others adopted UniWB decades ago. In the invariant "I'll just photograph at base ISO and adjust" scenario you have two risks: (1) that your raw converter actually can handle the math well for low bit values being moved significantly; and (2) did the highlights actually get near saturation?

Pragmatically—and my point about "just use ISO" is 100% pragmatic for the majority of users, which is why the camera makers include ISO as a user-settable function—it's simpler to use exposure tools and get the right brightness in the first place using ISO. Again, it's easier to verify that you've done the right thing in the field.

But I'm still waiting for someone to show me that they are getting significantly better results from following the invariant path. And when someone does, my next question is going to be about how long it took them to get those results.
The more interesting thing to me is the HLG approach, which is now being explored by Nikon and Sony in HEIC (Canon uses a different tonal method that's not directly what the P3 monitors will take advantage of). You made the comment about "boosting shadows and protecting highlights." Well, that's what proper HLG technique does directly. For images to be shown on HDR-type displays.
This thread seems to be pretty exclusively centered on raw shooting. The answer to the OP's question is rather different if we're considering alternative formats.
But that's another variable that's coming into play. Clearly the camera makers (and video makers) are looking at HLG like techniques to do effectively the same thing the invariant raw folk are doing, and to essentially make that pragmatic for the majority of users. They're not there yet, but they will be. At that point, we do have to ask whether there's significant benefit in using 14-bit raw versus 10-bit HLG done right.

My point in all of this is not to say one way is right and the other wrong, but to engage the discussion of benefit versus effort. The camera makers are trying to reduce your effort, which is why we have ISO in the first place (and it's absolutely necessary for JPEGs, after all).
OK, here's one: current AI-based NR solutions tend to turn pattern noise into "texture". It makes things worse, not better than conventional NR reduction solutions and significantly worse than a higher EV that requires less or no additional boosted lightness added in processing.
I would disagree with that statement. But now we're in a different discussion that deserves its own thread.
 
Now, if we were talking about the signal reaching the sensor, then the ISO 100 capture would have a grater magnitude of noise and a lower signal to noise ratio.
What ?

Anyway I found your explanations very convoluted and confusing.

I suggest the "colloquial" teminology remains, maybe this is more clear at the end.
Imagine that we are sending a pure sine wave tone through two different channels. Let’s call them Channel A and Channel B.

Out of Channel A we get a sine wave of 10 volts, but there is 1 volt of noise.

Out of Channel B, we get a sine wave of 100 volts but there is 4 volts of noise.

If you are concerned with the absolute magnitude of the noise, then that would be Channel B. 4 volts is greater than 1 volt.

However, we are more often concerned with the ratio of the signal to noise. Channel A has a ratio of 10 volts of signal to 1 volt of noise. That’s a 10:1 ratio.

Channel B has a ratio of 100 volts of signal to 4 volts of noise. That’s a 25:1 ratio.

Therefore we would normally say that Channel A is the noisier channel as it has a lower Signal to Noise ratio (10:1 vs. 25:1).
Another convoluted answer to hide the fact that you are wrong.

You said: "the ISO 100 capture would have a grater magnitude of noise and a lower signal to noise ratio."

In the scenario you described, it has higher exposure and the SNR is improved (=higer)

Simply admit it..
Yes. That was a typo. Thank you for catching it.
 
Now, if we were talking about the signal reaching the sensor, then the ISO 100 capture would have a grater magnitude of noise and a lower signal to noise ratio.
What ?

Anyway I found your explanations very convoluted and confusing.

I suggest the "colloquial" teminology remains, maybe this is more clear at the end.
Imagine that we are sending a pure sine wave tone through two different channels. Let’s call them Channel A and Channel B.

Out of Channel A we get a sine wave of 10 volts, but there is 1 volt of noise.

Out of Channel B, we get a sine wave of 100 volts but there is 4 volts of noise.

If you are concerned with the absolute magnitude of the noise, then that would be Channel B. 4 volts is greater than 1 volt.

However, we are more often concerned with the ratio of the signal to noise. Channel A has a ratio of 10 volts of signal to 1 volt of noise. That’s a 10:1 ratio.

Channel B has a ratio of 100 volts of signal to 4 volts of noise. That’s a 25:1 ratio.

Therefore we would normally say that Channel A is the noisier channel as it has a lower Signal to Noise ratio (10:1 vs. 25:1).
Another convoluted answer to hide the fact that you are wrong.

You said: "the ISO 100 capture would have a grater magnitude of noise and a lower signal to noise ratio."

In the scenario you described, it has higher exposure and the SNR is improved (=higer)

Simply admit it..
Yes. That was a typo. Thank you for catching it.
Maybe this is what happens when we make things too complicated.

But ok, thanks a lot for your clarification !
 
Bringing this back to photography, the pixels on your sensor essentially count photons.
No they don’t. The photo diode part of the pixel does does and then other transistors in the integrated circuit (the pixel) perform other tasks, including converting that analog information - which is just a tally of the number of light photons striking the photodiode - into a digital signal. Other processes are performed as well before that signal and the signals from all of the other millions of pixels around it is sent down the image formation pipeline. Exactly what is done varies from camera manufacturer to camera manufacturer and there are also differences between cameras from the same manufacturer. There are even differences between cameras that are closely related such as the Nikon Z 9 and Z 8.
 
Bringing this back to photography, the pixels on your sensor essentially count photons.
No they don’t. The photo diode part of the pixel does does and then other transistors in the integrated circuit (the pixel) perform other tasks, including converting that analog information - which is just a tally of the number of light photons striking the photodiode - into a digital signal. Other processes are performed as well before that signal and the signals from all of the other millions of pixels around it is sent down the image formation pipeline. Exactly what is done varies from camera manufacturer to camera manufacturer and there are also differences between cameras from the same manufacturer. There are even differences between cameras that are closely related such as the Nikon Z 9 and Z 8.
You say it’s “a tally of the number of light photons“, and I said it was essentially a count of the photons. Conceptually, we are not far apart, we just prefer different terminology.
 
It’s more than that. You are misrepresenting what happens at the pixel level.
 
Except that the visible noise hasn't gone down. The visibility of the noise has gone down.

Visibility of noise has decreased but noise has increased. I find it useful to distinguish between noisiness - which is the visibility of noise, and relative quantity noise. That way I don't end up saying thing that are the opposite of reality.

It can be counterintuitive that the least noisy photos are the ones with the most noise. But describing the noisiness of photos in terms such as the less noisy of two has less noise is just wrong.
Typically, in the context of noisy photographs, people generally use the term "noise" to refer to the signal to noise ratio,
Typically, when they do that, they do not realize that is what they are doing.
not the absolute magnitude of the noise.
I'd suggest that most people think that noisier photos have more noise, and that less noisy photos are less noisy because they have less noise, not because they have more signal. You know better, but most people don't.
When they say an image is nosier, they mean that it has a lower signal to noise ratio,
No they mean that it looks more noisy. We know that's because it has a lower SNR but most people who describe a photo as "noisier" think it has more noise. In fact they are more likely to say that it "has more noise" than they are to say it "is noisier" when describing a noisier photo.
not that the absolute value of the noise is greater.

This is nothing new with photography. In signal processing, a "noisy channel" is almost always taken to mean a channel with a low signal to noise ratio.
Signal processing in general isn't constrained to cases where the noise generally approaches the sqrt of the signal.
If the unusual case that they want to refer to the absolute magnitude of the noise, they would go out of their way to say that.
I think it is incumbent on you and I and people who know better to use terminology that is both understandable and technically correct at the same time. "Noisier" instead of "has more noise"; "less noisy" instead of "has less noise"; "too light" instead of "overexposed" for those cases where the lightness is due to unknown causes or due to too high an ISO or too much lightening in development. Using colloquial terminology in a technically incorrect sense is not necessary in most cases to make oneself properly understood. It is usually perfectly possible to use terminology such as I have suggested, be understood, be technically correct, and avoid furthering popular misconceptions.
Yes, it is important to be technically correct.

For instance, Consider two JPEG images of the same scene with the camera set to Auto. For the first JPEG, the camera was set to ISO 100. For the second it was set to ISO 12800. As the camera is set to Auto, it will use different settings of Aperture and/or shutter to produce the same image lightness for both images.

Most likely, the ISO 100 JPEG will look less noisy than the ISO 12800 JPEG.

Let’s consider the question as to which JPEG image has a grater magnitude of noise.

The technically correct answer is that the ISO 100 JPEG will have less noise.
No, that is not technically correct. You can't cite a technical source supporting it.

I see the distinction you are drawing, but it is baseless.

You ought to know that the SNR calculations one sees in sites like DxOMark are based on reading pixel values, not on somehow reading signal reaching the sensor.
Now, if we were talking about the signal reaching the sensor, then the ISO 100 capture would have a grater magnitude of noise and a lower signal to noise ratio. However we get a different answer if we are talking about JPEG images where the signal has been normalized to yield reasonable image lightness.

In our above example, where the camera was in automatic, the signal level in the two images have been normalized. This process also affects the noise level. By the time we are looking at JPEG images, the JPEG that visibly has more noise, probably does have more noise.

Therefore it is reasonable to say that an image that looks noisier, has more noise.
If you are talking about pixel values from the sensor, you are not talking about JPEG images.

By the time you get to the stage where you have a JPEG image the data has been manipulated quite a bit.

Consider two photos of a photo of a neutral gray wall. The camera is set to Full Auto, and the photographer has dialed in exposure compensation so the wall reads R=128, G=128, and B=128. One image is taken with the camera set to ISO 100, the other with the ISO set to 12,800.

By the time you get to the JPEG stage, the signal is 128,128,128 in both image files. In the ISO 12,800 image there will be more noise, and therefore more variation from that 128,128,128.

Therefore, in the JPEG files, the ISO 100 image has both less total noise and a greater signal to noise ratio.

.

Now, if you want to talk about the signals coming off the sensor, there will be a different answer, but I was talking about the noise in the resulting image file, not the noise in the raw processing phase.
 
It’s more than that. You are misrepresenting what happens at the pixel level.
Conceptually, the pixels produce a signal that increases with the number of photons captured. I think it i fair to day that the signal, in some way, represents the count of the photons seen.

Yes, it isn’t a simple integer that represents the exact number of photons, but I wasn’t trying to give a technical explanation of how it works, I was trying to give a rough conceptual overview.
 
It’s more than that. You are misrepresenting what happens at the pixel level.
Conceptually, the pixels produce a signal that increases with the number of photons captured. I think it i fair to day that the signal, in some way, represents the count of the photons seen.

Yes, it isn’t a simple integer that represents the exact number of photons, but I wasn’t trying to give a technical explanation of how it works, I was trying to give a rough conceptual overview.
As far as I know since university days, light is that portion of the photons in the electromagnetic spectrum that can be perceived by a human's visual system.

.

After an energetic photon knocks an electron off of a sensor pixel atom, the resulting positive charge can be read and be converted to a voltage which can be translated by the camera to a digital value that becomes the basis for the raw image.

Ancient memory, hopefully correct !!!

--
Charles Darwin: "ignorance more frequently begets confidence than does knowledge."
tony
 
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It’s more than that. You are misrepresenting what happens at the pixel level.
Conceptually, the pixels produce a signal that increases with the number of photons captured. I think it i fair to day that the signal, in some way, represents the count of the photons seen.

Yes, it isn’t a simple integer that represents the exact number of photons, but I wasn’t trying to give a technical explanation of how it works, I was trying to give a rough conceptual overview.
As far as I know since university days, light is that portion of the photons in the electromagnetic spectrum that can be perceived by a human's visual system.

After an energetic photon knocks an electron off of a sensor pixel atom, the resulting positive charge can be read and be converted to a voltage which can be translated by the camera to a digital value that becomes the basis for the raw image.

Ancient memory, hopefully correct !!!
Yes, the more visible photons that reach the sensor, the higher the output of the pixel.

Yes, the pixels are not sensitive to every wavelength. Furthermore, filters are typically used to remove wavelengths we don’t want reaching that pixel.

The question is whether it makes sense to characterize the conceptual job of the pixels, roughly speaking, as counting the photons. While the pixels don’t directly report a simple count, their output is very much influenced by the number of photons that they see.
 
Yes. It's an additional option. But what you're not seeing in this discussion is anything that shows how that option is clearly better, just assertions that it is.
Consider a high DR scene such as a church interior featuring important details and colors in the highlights (e.g., stained glass windows) and in the shadowed and poorly lit areas (e.g., elaborate woodwork, stonework, artwork, etc. or people).
As I wrote, it's an option to tackle a scene differently.
Not just differently...better (assuming you're shooting raw)! Within the invariant range of ISOs there's simply no advantage to bumping up the ISO and a definite highlight clipping downside for the stained glass windows.
But everyone's missing one of my points: is it significantly better to expose at base ISO and "recover" shadows or just use a higher ISO value (taking into account highlights).
You're doing a fine job of arguing against yourself by questioning the value of "expos[ing] at base ISO" and then immediately following that with your explanation (admission?) that you've been using uniWB for years, implying that you're using an ETTR-style exposure strategy. As I'm sure you understand, if you're ETTR'ing you should always "expose" at base ISO. The real question you should be asking: Is it ever "significantly better" to increase ISO once you've determined optimal raw exposure at base ISO? The answer, of course, is highly dependent on how much risk of highlight clipping, which is quite often irreversible in (post)processing, is worth the extremely modest read noise reduction benefit to be gained from modern cameras with ISO behavior that approaches invariance. On the one hand, there's very real, very difficult to fix clipping risk. On the other hand, there's very modest, and usually very successfully countered additional noise risk (more so, with the AI denoising).

The trends (reduced read noise in more recent sensor generations, multiple gain sensors, increasingly available/effective denoising options) clearly favors erring more and more on the side of just sticking at the lowest ISO levels for your camera's "invariant" ISO range(s) instead of relying on still too easily-fooled metering systems and cumbersome workarounds like uniWB and blinkies.
There's a reason why I and others adopted UniWB decades ago.
Yeah, so did I. I've long since abandoned uniWB except in a few special cases where critical color highlights are a significant concern. I still aggressively optimize exposure, but knowing my Oly EM1iii's ISO behavior and having extensively studied the fairly minimal benefits to be gained, I err on the conservative side of pushing ISO (or max'ing the upper limit of auto-ISO).
In the invariant "I'll just photograph at base ISO and adjust" scenario you have two risks: (1) that your raw converter actually can handle the math well for low bit values being moved significantly;
You've overstated that issue and have ignored the flip side of it, which is the problems of handling highlights that have gone non-linear or clipped in one or two channels. Your example of Adobe's limited WB control that sometimes causes issues with underwater images, for instance, is misplaced. To the extent it's problematic for a given WB requirement, it's going to be just as problematic for a comparable shot that's taken at a higher ISO that doesn't require an exposure adjustment in conversion. Regardless, the real solution isn't to abandon appropriate exposure and ISO setting but, rather, to create an appropriate custom DCP profile for such an extreme WB condition and using that in ACR/LR instead of one of Adobe's built in ones. Of course, the real irony here is that you raise this WB bogeyman at the same time you advocate for shooting with uniWB!
and (2) did the highlights actually get near saturation?
Once again, you've got the issue flipped the wrong way since the real risk of highlight saturation rests with the photographer who chooses to push ISO, not the one who's satisfied with sticking at base ISO with optimized exposure, but possible room left to pseudo-ETTR by pushing ISO.
Pragmatically—and my point about "just use ISO" is 100% pragmatic for the majority of users, which is why the camera makers include ISO as a user-settable function—it's simpler to use exposure tools and get the right brightness in the first place using ISO. Again, it's easier to verify that you've done the right thing in the field.
Well, it may be "100% pragmatic" for photographers who prioritize optimizing for JPEG capture, but it most certainly isn't pragmatic for photographers who prioritize optimizing for raw capture. I'm really rather surprised that someone with your level of experience would be confusing what ISO is and how/why it was implemented in cameras.
But I'm still waiting for someone to show me that they are getting significantly better results from following the invariant path. And when someone does, my next question is going to be about how long it took them to get those results.
See above.
The more interesting thing to me is the HLG approach, which is now being explored by Nikon and Sony in HEIC (Canon uses a different tonal method that's not directly what the P3 monitors will take advantage of). You made the comment about "boosting shadows and protecting highlights." Well, that's what proper HLG technique does directly. For images to be shown on HDR-type displays.
This thread seems to be pretty exclusively centered on raw shooting. The answer to the OP's question is rather different if we're considering alternative formats.
But that's another variable that's coming into play. Clearly the camera makers (and video makers) are looking at HLG like techniques to do effectively the same thing the invariant raw folk are doing, and to essentially make that pragmatic for the majority of users. They're not there yet, but they will be. At that point, we do have to ask whether there's significant benefit in using 14-bit raw versus 10-bit HLG done right.
Better DR control is not the only reason I shoot raw. If, however, you want to advocate for the RGB flavor of-the-month format, go right ahead, but that's not what this thread has been about.
My point in all of this is not to say one way is right and the other wrong, but to engage the discussion of benefit versus effort. The camera makers are trying to reduce your effort, which is why we have ISO in the first place (and it's absolutely necessary for JPEGs, after all).
Now, that's a statement of the obvious!
OK, here's one: current AI-based NR solutions tend to turn pattern noise into "texture". It makes things worse, not better than conventional NR reduction solutions and significantly worse than a higher EV that requires less or no additional boosted lightness added in processing.
I would disagree with that statement. But now we're in a different discussion that deserves its own thread.
Here are crops from the DPR studio scene ISO invariance 5-stop push shot for the D7100:

ISO 3200 with AI Noise Enhancement in ACR at default setting
ISO 3200 with AI Noise Enhancement in ACR at default setting

ISO 100 with +5 exposure adjustment and +50 luminance noise adjustment in ACR (no AI enhancement applied). All other settings same as the ISO 3200 shot.
ISO 100 with +5 exposure adjustment and +50 luminance noise adjustment in ACR (no AI enhancement applied). All other settings same as the ISO 3200 shot.

[ATTACH alt="ISO 100 with +5 exposure adjustment and AI Noise Enhancement at default (50) setting in ACR. All other settings same as the ISO 3200 shot. Note how the horizontal pattern noise is "enhanced" into horizontal streaks. "]3476432[/ATTACH]
ISO 100 with +5 exposure adjustment and AI Noise Enhancement at default (50) setting in ACR. All other settings same as the ISO 3200 shot. Note how the horizontal pattern noise is "enhanced" into horizontal streaks.
 

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... current AI-based NR solutions tend to turn pattern noise into "texture". It makes things worse, not better than conventional NR reduction solutions and significantly worse than a higher EV that requires less or no additional boosted lightness added in processing.
I was going to ask for an example, so I was happy to see this:
Here are crops from the DPR studio scene ISO invariance 5-stop push shot for the D7100:

ISO 3200 with AI Noise Enhancement in ACR at default setting
ISO 3200 with AI Noise Enhancement in ACR at default setting

ISO 100 with +5 exposure adjustment and +50 luminance noise adjustment in ACR (no AI enhancement applied). All other settings same as the ISO 3200 shot.
ISO 100 with +5 exposure adjustment and +50 luminance noise adjustment in ACR (no AI enhancement applied). All other settings same as the ISO 3200 shot.

[ATTACH alt="ISO 100 with +5 exposure adjustment and AI Noise Enhancement at default (50) setting in ACR. All other settings same as the ISO 3200 shot. Note how the horizontal pattern noise is "enhanced" into horizontal streaks."]3476432[/ATTACH]
ISO 100 with +5 exposure adjustment and AI Noise Enhancement at default (50) setting in ACR. All other settings same as the ISO 3200 shot. Note how the horizontal pattern noise is "enhanced" into horizontal streaks.
My question: Have you tested that with the AI noise reduction in tools other than ACR?
 
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Consider a high DR scene such as a church interior featuring important details and colors in the highlights (e.g., stained glass windows) and in the shadowed and poorly lit areas (e.g., elaborate woodwork, stonework, artwork, etc. or people). Assuming it's not desirable or practical to deal with the scene DR with flash or exposure bracketing, wouldn't the knowledge that your camera is (acceptably) "invariant" influence your decision on which ISO to use?
Very simply I try not to clip highlights anyway..

So even if I know the sensor is invariant, this does not make any differences in practice with the way I am shooting.
Consider also a hot sunny day where your subjects are perspiring with strong shadows being cast on most of their faces but strong, perhaps even near-specular highlights on their cheeks or foreheads or noses. Other important parts of the scene are also much darker than the highlights on subjects' faces. Do you want to take advantage of the "additional option" your camera's ISO "invariance" provides or do you just go with the higher auto ISO that your metering is defaulting to?
This is not really an "additional option".

An invariant sensor can also be seen as a sensor which can not improve at higher ISO.. in a way, it gives you fewer options to improve SNR.

Let' imagine yoh show me an image where you had good results with your technic using base ISO. In my case, I would have used let's say ISO 300 but without blowing highlights. So what ?? Your image won't be better, at best it will be as good provided the sensor is invariant. Where is the supposed additional option ? Where is the "creativity" ? Really don't get it..

The only thing to consider is to look for instance how the sensor performs at base ISO (for DR, noise,..). If I have a variant sensor which is better than your invariant sensor, I will get better results in the scenarios you describe, whether the sensor is invariant or not. So what really matters is to see how the sensor performs.

The hype about invariant sensors is a nonsense imho as I said in other posts in this thread.
 
... current AI-based NR solutions tend to turn pattern noise into "texture". It makes things worse, not better than conventional NR reduction solutions and significantly worse than a higher EV that requires less or no additional boosted lightness added in processing.
I was going to ask for an example, so I was happy to see this:
Here are crops from the DPR studio scene ISO invariance 5-stop push shot for the D7100:

ISO 3200 with AI Noise Enhancement in ACR at default setting
ISO 3200 with AI Noise Enhancement in ACR at default setting

ISO 100 with +5 exposure adjustment and +50 luminance noise adjustment in ACR (no AI enhancement applied). All other settings same as the ISO 3200 shot.
ISO 100 with +5 exposure adjustment and +50 luminance noise adjustment in ACR (no AI enhancement applied). All other settings same as the ISO 3200 shot.

[ATTACH alt="ISO 100 with +5 exposure adjustment and AI Noise Enhancement at default (50) setting in ACR. All other settings same as the ISO 3200 shot. Note how the horizontal pattern noise is "enhanced" into horizontal streaks."]3476432[/ATTACH]
ISO 100 with +5 exposure adjustment and AI Noise Enhancement at default (50) setting in ACR. All other settings same as the ISO 3200 shot. Note how the horizontal pattern noise is "enhanced" into horizontal streaks.
My question: Have you tested that with the AI noise reduction in tools other than ACR?
Good question. I've not been using DXO DeepPrime much since Adobe's release of the AI denoising in ACR's Enhance module. Here's what DeepPrime does (I don't have PhotoLab 6, so I can't test it with XD):

DeepPrime at +25; exported as a DNG with Denoise and Optical Corrections only option. Opened in ACR/PS with default options.
DeepPrime at +25; exported as a DNG with Denoise and Optical Corrections only option. Opened in ACR/PS with default options.

Definitely less extreme than ACR's AI Denoise. However, that raises the question of how well DeepPrime does with preserving real linear detail at the same settings:

 Left=DeepPrime; Right=ACR's AI Denoise
Left=DeepPrime; Right=ACR's AI Denoise

DeepPrime seems to be less sensitive/aggressive to generating this kind of detail, for better or worse.
 
... current AI-based NR solutions tend to turn pattern noise into "texture". It makes things worse, not better than conventional NR reduction solutions and significantly worse than a higher EV that requires less or no additional boosted lightness added in processing.
I was going to ask for an example, so I was happy to see this:
Here are crops from the DPR studio scene ISO invariance 5-stop push shot for the D7100:

ISO 3200 with AI Noise Enhancement in ACR at default setting
ISO 3200 with AI Noise Enhancement in ACR at default setting

ISO 100 with +5 exposure adjustment and +50 luminance noise adjustment in ACR (no AI enhancement applied). All other settings same as the ISO 3200 shot.
ISO 100 with +5 exposure adjustment and +50 luminance noise adjustment in ACR (no AI enhancement applied). All other settings same as the ISO 3200 shot.

[ATTACH alt="ISO 100 with +5 exposure adjustment and AI Noise Enhancement at default (50) setting in ACR. All other settings same as the ISO 3200 shot. Note how the horizontal pattern noise is "enhanced" into horizontal streaks."]3476432[/ATTACH]
ISO 100 with +5 exposure adjustment and AI Noise Enhancement at default (50) setting in ACR. All other settings same as the ISO 3200 shot. Note how the horizontal pattern noise is "enhanced" into horizontal streaks.
My question: Have you tested that with the AI noise reduction in tools other than ACR?
Note that D7100 is an extreme case of ISO invariance. No contemporary camera is like that.
 
... current AI-based NR solutions tend to turn pattern noise into "texture". It makes things worse, not better than conventional NR reduction solutions and significantly worse than a higher EV that requires less or no additional boosted lightness added in processing.
I was going to ask for an example, so I was happy to see this:
Here are crops from the DPR studio scene ISO invariance 5-stop push shot for the D7100:
My question: Have you tested that with the AI noise reduction in tools other than ACR?
Good question. I've not been using DXO DeepPrime much since Adobe's release of the AI denoising in ACR's Enhance module. Here's what DeepPrime does (I don't have PhotoLab 6, so I can't test it with XD):

Definitely less extreme than ACR's AI Denoise. However, that raises the question of how well DeepPrime does with preserving real linear detail at the same settings:

Left=DeepPrime; Right=ACR's AI Denoise
Left=DeepPrime; Right=ACR's AI Denoise

DeepPrime seems to be less sensitive/aggressive to generating this kind of detail, for better or worse.
I prefer the tonality of DeepPrime. However I am almost never conserned about noise in spite of the fact I very often shoot low light theatre and dance. For those rare situations (IMHO) needing noise reduction my ancient NeatImage gives more than adequate high quality noise reduction. Normally I simply a accept noise as part of the photographic process.

Unedited out of camera other than minor crop. Old Canon 14 years ago
Unedited out of camera other than minor crop. Old Canon 14 years ago

--
Charles Darwin: "ignorance more frequently begets confidence than does knowledge."
tony
 
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Except that the visible noise hasn't gone down. The visibility of the noise has gone down.

Visibility of noise has decreased but noise has increased. I find it useful to distinguish between noisiness - which is the visibility of noise, and relative quantity noise. That way I don't end up saying thing that are the opposite of reality.

It can be counterintuitive that the least noisy photos are the ones with the most noise. But describing the noisiness of photos in terms such as the less noisy of two has less noise is just wrong.
Typically, in the context of noisy photographs, people generally use the term "noise" to refer to the signal to noise ratio,
Typically, when they do that, they do not realize that is what they are doing.
not the absolute magnitude of the noise.
I'd suggest that most people think that noisier photos have more noise, and that less noisy photos are less noisy because they have less noise, not because they have more signal. You know better, but most people don't.
When they say an image is nosier, they mean that it has a lower signal to noise ratio,
No they mean that it looks more noisy. We know that's because it has a lower SNR but most people who describe a photo as "noisier" think it has more noise. In fact they are more likely to say that it "has more noise" than they are to say it "is noisier" when describing a noisier photo.
not that the absolute value of the noise is greater.

This is nothing new with photography. In signal processing, a "noisy channel" is almost always taken to mean a channel with a low signal to noise ratio.
Signal processing in general isn't constrained to cases where the noise generally approaches the sqrt of the signal.
If the unusual case that they want to refer to the absolute magnitude of the noise, they would go out of their way to say that.
I think it is incumbent on you and I and people who know better to use terminology that is both understandable and technically correct at the same time. "Noisier" instead of "has more noise"; "less noisy" instead of "has less noise"; "too light" instead of "overexposed" for those cases where the lightness is due to unknown causes or due to too high an ISO or too much lightening in development. Using colloquial terminology in a technically incorrect sense is not necessary in most cases to make oneself properly understood. It is usually perfectly possible to use terminology such as I have suggested, be understood, be technically correct, and avoid furthering popular misconceptions.
Yes, it is important to be technically correct.

For instance, Consider two JPEG images of the same scene with the camera set to Auto. For the first JPEG, the camera was set to ISO 100. For the second it was set to ISO 12800. As the camera is set to Auto, it will use different settings of Aperture and/or shutter to produce the same image lightness for both images.

Most likely, the ISO 100 JPEG will look less noisy than the ISO 12800 JPEG.

Let’s consider the question as to which JPEG image has a grater magnitude of noise.

The technically correct answer is that the ISO 100 JPEG will have less noise.
No, that is not technically correct. You can't cite a technical source supporting it.

I see the distinction you are drawing, but it is baseless.

You ought to know that the SNR calculations one sees in sites like DxOMark are based on reading pixel values, not on somehow reading signal reaching the sensor.
Now, if we were talking about the signal reaching the sensor, then the ISO 100 capture would have a grater magnitude of noise and a lower signal to noise ratio. However we get a different answer if we are talking about JPEG images where the signal has been normalized to yield reasonable image lightness.

In our above example, where the camera was in automatic, the signal level in the two images have been normalized. This process also affects the noise level. By the time we are looking at JPEG images, the JPEG that visibly has more noise, probably does have more noise.

Therefore it is reasonable to say that an image that looks noisier, has more noise.
If you are talking about pixel values from the sensor, you are not talking about JPEG images.

By the time you get to the stage where you have a JPEG image the data has been manipulated quite a bit.

Consider two photos of a photo of a neutral gray wall. The camera is set to Full Auto, and the photographer has dialed in exposure compensation so the wall reads R=128, G=128, and B=128. One image is taken with the camera set to ISO 100, the other with the ISO set to 12,800.

By the time you get to the JPEG stage, the signal is 128,128,128 in both image files. In the ISO 12,800 image there will be more noise, and therefore more variation from that 128,128,128.

Therefore, in the JPEG files, the ISO 100 image has both less total noise and a greater signal to noise ratio.
Thank you Michael. You've definitely given me something to think about here. I'm sorry for my earlier reaction.

If I understand you correctly, you are saying the normalization process of applying ISO at two different levels for two different images takes different signal levels from the sensor and transforms them into the same signal level in the two image files. It also preserves the SNR , but because the SNR and signal have both been multiplied by the same constant, the square root relationship of noise to signal that we saw in the signal from the sensor no longer applies.

I'm going to have to take some time to be sure I understand the ramifications.
.

Now, if you want to talk about the signals coming off the sensor, there will be a different answer, but I was talking about the noise in the resulting image file, not the noise in the raw processing phase.
 
I’ve never seen an example where two shots have no difference, could you point me to one?

In my experience whether you raise ISO in the camera or push sliders in Photoshop the visible noise goes up, contrast rises, color falls apart, and dynamic range collapses in a very noticeable way at every additional stop.

It may not be apparent to everyone but for what I do it’s not acceptable. Yes for some assignments I have to shoot at ISO 6400 but I am never excited with the results.

And I’ve never seen any documentation from the camera manufacturers saying the images from their cameras are pixel-for pixel identical at these supposedly invariant ISOs; that would be a huge selling point so if they’re not saying it there might be more to the story.

On the other hand one could truthfully argue that once you raise the ISO past 64 the image quality is so bad that nothing you do to it can really make the image any worse.
Bill Ferris wrote

For anyone who doubts this, simply look at and compare the hundreds of photos which have been posted to DPReview forums over the last decade demonstrating the reality that photos pushed multiple stops in post are indistinguishable from photos made at higher ISOs when both photos were made using ISOs within a camera's invariant range.
 
Thank you Michael. You've definitely given me something to think about here. I'm sorry for my earlier reaction.

If I understand you correctly, you are saying the normalization process of applying ISO at two different levels for two different images takes different signal levels from the sensor and transforms them into the same signal level in the two image files. It also preserves the SNR , but because the SNR and signal have both been multiplied by the same constant, the square root relationship of noise to signal that we saw in the signal from the sensor no longer applies.

I'm going to have to take some time to be sure I understand the ramifications.
Yes, that's what I am saying. The mapping from the captured signal to the JPEG generally preserves the SNR. The camera does add a little additional noise, but in many cases it is not a significant amount.

Getting back to the OP's question, some cameras add less noise when the camera is set to higher ISO values. Therefore there can be some advantage to selecting a higher ISO, rather than just lightening the image in post production.

Generally lightening the image in post production lightens the image, but doesn't change the SNR.
 
I’ve never seen an example where two shots have no difference, could you point me to one?

In my experience whether you raise ISO in the camera or push sliders in Photoshop the visible noise goes up, contrast rises, color falls apart, and dynamic range collapses in a very noticeable way at every additional stop.

It may not be apparent to everyone but for what I do it’s not acceptable. Yes for some assignments I have to shoot at ISO 6400 but I am never excited with the results.

And I’ve never seen any documentation from the camera manufacturers saying the images from their cameras are pixel-for pixel identical at these supposedly invariant ISOs; that would be a huge selling point so if they’re not saying it there might be more to the story.

On the other hand one could truthfully argue that once you raise the ISO past 64 the image quality is so bad that nothing you do to it can really make the image any worse.
The key is to understand that exposure (the light reaching the sensor) is not necessarily tied to the ISO setting.

Usually, if you take an ISO 100 capture and an ISO 800 capture, you will use use different exposures. Perhaps f/4 for the ISO 100 capture and f/11 for the ISO 800 capture. In that typical case, you have selected a lower exposure (less light) for the ISO 800 exposure. That lower exposure results in more "shot noise" (the noise inherent in the quantum nature of light) and therefore the ISO 800 image looks noisier.

But that's not your only choice. You could have used the same aperture (f/11) and shutter for both the ISO 100 capture and the ISO 800 capture. Obviously, the camera produced ISO 100 JPEG will look dark. But you can easily lighten up the image when processing the raw file.

In that case, you will typically find that the lightened ISO 100 image has just about the same visible noise as the ISO 800 capture.
 

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