The tone of the article stands out to me; not much in the way of exaggeration or opinions on “the best” way to do a certain thing, but an almost dispassionate tour of some of the different ways we’ve thought about light and dark artistically, over time. Thoroughly enjoyed the read!
Agree on the nice historical summary. The end of the final paragraph struck me in particular:
“My photos are a collaboration between me and the algorithm designers and camera manufacturers, and they reflect a combination of aesthetic decisions made by each of us.”
The one downside of taking pictures with such a strongly opinionated technology is that your pictures are going to look like everyone else’s (or increasingly just weird). Ansel Adams developed his darkroom technique over decades - and as the author mentions, applying them took hours of meticulous labor. So his output really did look different from most other peoples’.
You can still differentiate your photographs on the basis on their subject matter, of course. But if everyone is shooting out of the same algorithmic pipeline, making your pictures look better technically is going to be increasingly hard. (And given current limitations, someone knowledgeable in the field today can still usually tell the difference between photographs taken with good lenses carefully deployed and cell phone output. But it’s unclear how long that will be true.)
Lenses can be added to cell phones through 3rd party attachments. And aren't these ML options able to be turned off? It should make the phone camera much more like a standard camera.
Doesn’t the same criticism apply to the aesthetic choices baked into film? It seems to me that the amount of technical expertise it takes to post process a phone-captured RAW file in Lightroom compares favorably to the amount of expertise it would take to have a physical dark room and tools to dodge and burn. If anything, it seems to me that it’s gotten easier to master the tools necessary to make your pictures look technically better.
Yes and for during the height of the film era what film stock you chose, along with your choice of push/pull on the stated ISO levels, was part of any project’s aesthetic choices.
It is immensely easier to do in light room what previously took hours in a dark room and years to master. We can now spend more time thinking about specific aesthetic choices and less time making test strips of 1 stop intervals on a small strip of the sky to correctly dial in exposure. That’s a process that can take a very long time, involve lots of chemicals, and expose you to some carcinogens.
It seems to me there must be some kind of error in color calibration of most cameras. They make shadows much darker than they are, and bright areas much brighter than they are. It's not from a lack of dynamic range.
Colour transparency film (e.g. Fuji Velvia -- RVP50) shows the same thing as clearly.
You basically can't map real world light into the dynamic range of a typical camera without causing some of this experience, can you?
The question is how you determine how dark shadows should be -- your brain is doing a lot of work to hide from you the tricks it uses to make shadows appear less dark than they might be with a linear response.
Or even how they would look with a non-linear response that is even across the "frame"; your brain is doing localised dodge/burn type work, constantly.
Camera manufacturers have "tastemakers" for this stuff on digital, just as film manufacturers used to have them for film.
It is different because it is obvious that shadows are darker than in reality while highlights are much brighter than in reality.
Any brain filtering would have to affect the photos as well, even if it was true.
No common image format uses linear response. It would explain this problem if cameras treat them as linear.
Maybe they should just make the cameras take physically correct colors, instead of relying on people, as the typical person will always choose extreme contrast that will make the camera unusable. (and can be easily increased in editing)
> Any brain filtering would have to affect the photos as well, even if it was true.
Not when the dynamic range of reality is much greater than that of photographs, and your visual system is one of the best visual processors in existence. It’s like reducing a 24-bit image to 16-bit - the image is “good enough” to identify the subject, but it is quite lossy. Photography itself is a lossy process.
What is "brain filtering" and why would you think either film or digital can reproduce the same visual effect as our eyes see?
Our brain does a perceptual aggregation of multiple frames and inputs. This is not how cameras work.
Also "make cameras take physically correct colors" is impossible unless you're talking about spectral capture, which is orders if magnitudes more complex. If you're using just RGB photosites AND RGB displays, there is no such thing as physically correct colors. Everything will just be a mapping at best, with the best that color science experts can actually provide.
The one I was replying to talked about brain processing. Whatever it is doesn't need to and shouldn't be reproduced in photography as the protograph gets processed just like everything else when you look at it.
Reality --> eye --> "brain filter"
Reality --> photo --> eye -> "brain filter"
Cameras should only record the colors as accurately as possible. Or if you want to nitpick again, so that the photo stimulates the eye receptors identically to whatever was captured.
they already do that to the best of our abilities.
Color is incredibly complex. It's easy to say "we should capture it as accurately as possible" but I don't think you fully comprehend the high complexity involved.
Your concept of matching eye receptors is wrong too. Color is perceptual and subjective. Your perception of color is based on your upbringing, your genetics, your environment, your own mental faculties, your mental state etc...
What is accurate? Your eyes see some spectral energy, your rods and cones convert those to signals, your brain then adds that into an aggregate set of information that it's constantly infilling and, most importantly, guessing about.
You can't guarantee that multiple people see color the same.
Now even if a camera could hypothetically capture an image accurately to the real world (IMHO only possible with a hypothetical full spectrum sensor), how would you store it? The second you convert it to RGB data it needs a perceptual conversion to the bit depth of the data format.
Now even if you have a file format that can efficiently represent this, you'd also need full spectrum displays so that we could beam that exact color to your retinas.
Color science is incredibly complex. You're trying to trivialize it into matching your own narrow perception of color.
It's physically impossible for a photo to send the same photons into the eye as the original scene did - imagine taking a photo outdoors in sunlight and then viewing that photo indoors, the whitest possible parts of the photo will be literally orders of magnitude darker than the original scene. Similarly you can't reproduce the same colours because you don't have all of the colours available (e.g. there's no way a computer screen using RGB pixels can reproduce the precise wavelength that a sodium lamp gives out). Trying to reproduce the experience of viewing the original scene is the best we can do, and that requires not just physics but biology and psychology. You talk about "eye receptors", but the line where the eye ends and the brain begins is actually very fuzzy - ontogenically your eyes are part of your brain, and the signals passing from eyes to brain are already in a "compressed form" where e.g. a straight line is represented by a single nerve impulse.
If you have never done this before, I absolutely recommend -- while it is still possible to do this in a practical way -- getting a cheap film camera, getting hold of a proper incident light meter (like a Sekonic L-208 or L-308), and shooting some Fuji Velvia 50 or Provia 100F. Or if you can find it, some modern Ektachrome.
For example you might want to go to a beach or a park and shoot throughout the day on a bright day. Put people or objects in the foreground and then shoot them with either the light behind you or in front. Use the incident metering dome to meter the light
(you'll need to look this up, but the broad point of it is you stand in the same light as your subject and point the meter into the light, rather than at your subject)
Once you see what transparency film does in high-contrast situations I think you'll better understand what I'm trying to get across.
I don't think shadows are darker than in reality, but instead don't have their detail captured, or get swamped out by high black levels on screens or glare in the viewing environment. Also highlights get clipped at a much lower level than in reality (photographs of suns aren't eye-searing unlike the real thing).
There's something off about the brightness sensitivity curves, if I can dial shadow controls way way up and salvage an otherwise botched, underexposed photo, why is it that I have to do so manually?
The dynamic range is clearly there. And we're not talking about such ridiculous values that the sensor noise becomes prominent.
You can do that correction in that situation because you've looked at the image, you know what it is meant to be, and you can decide on a set of adjustments that produce something that approximates what you want, perceptually.
But without truly extensive scene knowledge, cameras can't do that automatically, and they also can't know what information that is important to the photographer that they'd be affecting if they did.
Cameras have to try to ascertain what would be middle grey in a scene and then apply a general purpose tone curve to an image, but they do not know what is in the scene.
They can't even know for sure if the photo they are being asked to take is properly exposed by any absolute definition, in fact.
[I cut out a lot of this because I don't think it's going to be easy to complete the explanation here]
No, the problem is VERY OBVIOUSLY more severe than that. It's really as if the images were treated as linear, which they are not. (they use gamma correction)
This is also incorrect and trivializing of the color science. Images may use gamma correction, they may not. Trying to describe it in terms of gamma is like trying to describe food in terms of saltiness alone. You're ignoring tons of other factors.
Sure, and any meal you eat will have a salt content (possibly zero). Doesn't mean that that tells you all the things that could be wrong or right about the meal.
You're missing the point. You can't ONLY describe color spaces in gamma differences.
Gamma is just a single element of a color space. The whole trivializing sRGB into being a 2.2 Gamma versus linear is an over simplification that ignores gamut , white point, bit depth and more.
That's my point. You're trivializing what color is because you clearly have not dealt with it at scale.
No I'm not doing that, there seems to be some problem specifically there. Either the values are converted incorrectly, or not at all, effectivelly stretching about 8 fstops into the 11.6 (slightly less for video) f-stops of sRGB.
You can download an alternate color scheme from Technicolor for Canon cameras that makes the colors appear fairly reasonable.
I meant using gamma as a conversion function. There's a whole world of color transformations outside of just gamma.
Gamma is just one of many transformations, and you can have two color spaces with identical gamma transforms, but different gamuts, white points etc...
I think a lot of people were misunderstanding my comment. I never meant to imply that gamma is the only important consideration in color perception, I was only reacting to the statement that it was optional. Even color spaces that don't use gamma (i.e. are linear) must have a gamma applied before you can view them.
gamma correction is compression, sacrificing data in regions where the eye is less sensitive for more precision in the sensitive ranges. images would look the same without it, you'd just be wasting bits encoding differences that the eye can't see
That is exactly what is happening when you lack dynamic range.
Say that your eye is sensitive from light intensity 0 to 100 in some units, but your camera sensor only handles 40 to 60. That means that everything under 40 will be mapped to black, and everything above 60 will be mapped to white.
No, that does not make any sense. That should result in 40, and everything darker resulting in 40, while 60 and everything brighter resulting in 60. But what you can see is that 40 results in 0, and 60 resulting in 100. That should never happen unless there is an error in processing.
Only the picture file format should limit what range you can save with any modern camera.
No it doesn't make sense. You should not be able to capture anything darker than 40, or brighter than 60 if you are limited to 40-60. (actually by the file format, not the sensor, sensors today have higher dynamic ranges than 8 bit sRGB) It should not turn 40 into 0 and 60 into 100.
In real life, a logarithmic brightness scale (which is how human perception works) goes from negative infinity (zero energy) to positive infinity (infinite energy) – excluding both endpoints. 0 is not the bottom, and 100 is not the top.
In real life, photographs are printed on paper. The brightness of light reflecting off paper depends not only on the colour of the paper, but on the brightness of the illumination. (Likewise, photographs displayed on a computer monitor depend on the screen's brightness.)
In real life, human brightness perception depends on the brightness of the environment. An LED can look bright in the dark and dim in sunlight, and range dim to medium to bright on a cloudy day without anyone really noticing that the clouds between them and the sun are thicker or thinner.
In real life, there is no 0. There is no 100. Your comment doesn't make any sense.
Right. Metering is even now with scene programs and AI still basically a complicated negotiation about establishing middle grey -- when there may be no perceptual middle grey in the scene at all (black cat in coal bin, polar bear in snow)
The narrow band of sensitivity of a film or sensor has to be sort of moved to where it is needed (by controlling how much light gets in or for how long) according to the result the photographer is likely to want from their photo.
Even the most basic of film dead-reckoning methods -- Sunny 16 -- relies on subjective input from the photographer:
It's trivial to take an image editor and any existing image that is as you describe, and adjust the black point to 40 "percent" and white to 60%. It won't look more correct or realistic at all.
That of course depends on how you show it on the screen. You can of course show those part of the sensor that didn’t register anything (less than 40) as grey, and everything than saturated the sensor as a bit lighter grey. But people don’t tend to like the look of those pictures very much, and they definitely don’t look more natural than the conventional processing.
The main limitation isn’t the file format. The main limitation is the sensor. On the lower end, it is noise in different forms that overwhelm the very weak signal from dark areas. On the higher end, the sensors get saturated, that is, the semi-conductor bucket for the charges that is released by the photons get full.
And then the experience of the picture is of course limited by the medium that is used to display it. Even the best screens can’t show even a small fraction of the contrast that the eye experiences outdoors on a sunny day. And don’t mention printed media.
It's not the the camera that lacks dynamic range. It's your screen.
There's a fundamental problem with photography: a scene can contain up to 20 EV of dynamic range. Your camera can capture up to 14 EV. But your screen or a print can only depict 5-10 EV.
So something has to give. The camera capture is usually fine, only excluding the brightest highlights like the sun itself, and the darkest shadows, both of which we don't expect to contain detail anyway. But mapping the rest into the (let's say) 8 EV of available dynamic range of the screen is a problem.
Film does it in two ways: it rolls of highlights and shadows smoothly, preserving mid-tone contrast while compressing (and desaturating) extreme tones. Secondly, chemical diffusion enhances local contrast, while reducing global contrast, a bit like the "clarity" slider in Lightroom.
Smart phone cameras do something similar, with HDR image fusion, local contrast, and tone mapping.
Which is why, ultimately, only an edited picture can represent the experience of viewing a natural scene. The full tonal range of the scene can not be displayed. We have to rely on a somewhat artificial compressed rendition instead. But that's not a fault of the camera, or even the screen. But simply the result of showing an emissive reality on an (assumed) reflective medium. To me, it's the same perceptual unreality as projecting a 3D scene onto a 2D medium.
To me, it's what makes photography (and visual arts in general) interesting. They don't show reality, but a depiction of reality. And in that crop, project, compress, lies interpretation and expression.
No that can't be what's happening. You would expect contrast to be lost, not increased, if that was the issue.
8bit sRGB can contain 11.6 f-stops of dynamic range, and it is no longer enough for modern screens.
There must be a longstanding bug somewhere. It would not be the first time it happened. There was a chroma decoding bug in almost all DVD players. A very similar issue to this, antialiasing in CGI used to be calculated without gamma, until GPUs got fast enough to use it and I suppose that someone started looking into why it performs worse than expected.
Talking about film is particularly complicated, as film does not have an entirely linear response to light. This is called reciprocity failure and means that you often need to expose way longer than 2x the time to have the effect of 2x the light.
For digital, the data directly from camera sensors almost always needs some correction, de-mosaicing or massaging to generate an image viewable on a screen. This requires the camera to make what ends up being an aesthetic decision on what the photo looks like. Detail isn’t just how bright or how dark, but also the available gradients in between. This means there are cases where the dynamic range is automatically expanded (instead of clipped) and contrast unnaturally increased in order to have a photo that isn’t just mud.
Ultimately, this means that technical considerations map directly to artistic ones, and there is no objectively correct image from sensor data. The idea that a ‘no filter’ picture conveys some kind of divine truth is a myth.
Good point about the meaninglessness of a “no filter” concept. The article is very interesting in regard to lightness mapping, and there a another, related subject of hue mapping. This is a good part of the reason why pictures from different camera brands look different.
Your description of reciprocity failure is not quite right. The idea is that if you double the time the shutter is open and also decrease the aperture by one stop, you should not change the amount of light hitting the film (you will change other things, of course). The overall brightness should be the same when you make these “reciprocal” adjustments. This does in fact hold pretty well within a certain range of shutter speeds. Reciprocity failure occurs at longer or smaller speeds, where the reciprocal relationship doesn’t quite work.
Night photography, pinhole photography and a number of other common applications absolutely do encounter perceivable reciprocity failure, so there’s nothing wrong with my description.
Does a “raw” picture convey a divine truth? (Taking “divine truth” here to mean “analog sensor’s signal modulo the specified bit depth and some linear transform”)
The raw file contains light level recordings affine to the real scene illumination. (The black point is raised, which is why it's affine, not linear). (Assuming no bright pixels are clipped).
Each rgb channel is a filtered spectrum. But note that the color filters are essentially arbitrary, and only roughly correspond to the color filters of your eyes or your screen.
Also note that some cameras pre-process even raw data, for example with vignetting correction or noise reduction. Some phones even do image fusion and color correction, then re-rawify the data by mosaicing and linearization.
The point is that this is not a linear transform. To make the captured raw data look like a normal photo, a number of steps need to happen and several of those steps are about tricking human brains into believing the photo matches what your eyes would have perceived. These steps aren't actually linear because of a dynamic range mismatch between your eyes, the camera sensor and the output medium (screen and paper).
It's a game of fitting the captured scene with e.g. 11 stops of dynamic range to an output medium that has maybe 5 or 6 stops of dynamic range in order to trick human eyes with closer to 20 stops of dynamic range into believing what it sees on the print is "real/plausible". That is of course a very subjective process that involves a lot of choices regarding how to shape your curves and compress the available data.
Additionally, human brains do "funny" things with colors and actually re-construct/imagine things that aren't there. Getting the white balance and color grading "right" is another set of steps and what is right depends both on the conditions under which you capture the scene as under which conditions you view the end result.
Most phone cameras and in camera processing software algorithms for all of this that produce a certain look that is pleasing under most circumstances. But those are basically just a hard coded interpretation of the raw data. The point of post processing is having finer control over that process and the ability to use more expensive/better algorithms.
HDR capture (preserving more than 8 bits of light level, preserving meaningful detail in the shadows and not clipping highlights) preserves more of a scene than non-HDR JPEGs. Tone-mapping is the "tasteless HDR effect" which I have mixed feelings about (and can absolutely be done poorly, resulting in light halos around darker objects).
I'm surprised article claims that photography and film are no longer 'racist'. Most of my photos are underexposing dark complexions. It might be to do with limited dynamic range though, but still exists.
“Racist” is being used metaphorically. The choice of film chemistry to use will affect what sort of faces are captured well, and what sort of faces are captured poorly.
Quite a topical article, considering the controversy around how they made a potentially great Batman movie unwatchable by turning large parts of it into a radio drama where you can't see anything and have to figure out what's happening with nothing but your ears.
So often I cannot understand what people are saying!
As an examples, I was watching the show '1883' and half the time I cannot understand the dialog!
Now I have the most expensive best new Sony 65" you can buy, so I'd expect the sound to be at least half decent. So it's not my out-of-the-box speakers.
I feel like I'm constantly having to turn the TV up!
Some Googling had people on forums suggesting it's 'muddy mixing' whatever that is, and that shows are now mixed for Surround Sound.
However when I watch a 'normal' TV show like South Park or an average British SitCom, I can understand every word.
The situations is bonkers and its turning me off even bothering to try and watch some shows!
64 comments
[ 2.8 ms ] story [ 138 ms ] thread“My photos are a collaboration between me and the algorithm designers and camera manufacturers, and they reflect a combination of aesthetic decisions made by each of us.”
The one downside of taking pictures with such a strongly opinionated technology is that your pictures are going to look like everyone else’s (or increasingly just weird). Ansel Adams developed his darkroom technique over decades - and as the author mentions, applying them took hours of meticulous labor. So his output really did look different from most other peoples’.
You can still differentiate your photographs on the basis on their subject matter, of course. But if everyone is shooting out of the same algorithmic pipeline, making your pictures look better technically is going to be increasingly hard. (And given current limitations, someone knowledgeable in the field today can still usually tell the difference between photographs taken with good lenses carefully deployed and cell phone output. But it’s unclear how long that will be true.)
It is immensely easier to do in light room what previously took hours in a dark room and years to master. We can now spend more time thinking about specific aesthetic choices and less time making test strips of 1 stop intervals on a small strip of the sky to correctly dial in exposure. That’s a process that can take a very long time, involve lots of chemicals, and expose you to some carcinogens.
I love film photography but it is laborious.
Colour transparency film (e.g. Fuji Velvia -- RVP50) shows the same thing as clearly.
You basically can't map real world light into the dynamic range of a typical camera without causing some of this experience, can you?
The question is how you determine how dark shadows should be -- your brain is doing a lot of work to hide from you the tricks it uses to make shadows appear less dark than they might be with a linear response.
Or even how they would look with a non-linear response that is even across the "frame"; your brain is doing localised dodge/burn type work, constantly.
Camera manufacturers have "tastemakers" for this stuff on digital, just as film manufacturers used to have them for film.
Any brain filtering would have to affect the photos as well, even if it was true.
No common image format uses linear response. It would explain this problem if cameras treat them as linear.
Maybe they should just make the cameras take physically correct colors, instead of relying on people, as the typical person will always choose extreme contrast that will make the camera unusable. (and can be easily increased in editing)
Not when the dynamic range of reality is much greater than that of photographs, and your visual system is one of the best visual processors in existence. It’s like reducing a 24-bit image to 16-bit - the image is “good enough” to identify the subject, but it is quite lossy. Photography itself is a lossy process.
Our brain does a perceptual aggregation of multiple frames and inputs. This is not how cameras work.
Also "make cameras take physically correct colors" is impossible unless you're talking about spectral capture, which is orders if magnitudes more complex. If you're using just RGB photosites AND RGB displays, there is no such thing as physically correct colors. Everything will just be a mapping at best, with the best that color science experts can actually provide.
Reality --> eye --> "brain filter"
Reality --> photo --> eye -> "brain filter"
Cameras should only record the colors as accurately as possible. Or if you want to nitpick again, so that the photo stimulates the eye receptors identically to whatever was captured.
Color is incredibly complex. It's easy to say "we should capture it as accurately as possible" but I don't think you fully comprehend the high complexity involved.
Your concept of matching eye receptors is wrong too. Color is perceptual and subjective. Your perception of color is based on your upbringing, your genetics, your environment, your own mental faculties, your mental state etc... What is accurate? Your eyes see some spectral energy, your rods and cones convert those to signals, your brain then adds that into an aggregate set of information that it's constantly infilling and, most importantly, guessing about.
You can't guarantee that multiple people see color the same.
Now even if a camera could hypothetically capture an image accurately to the real world (IMHO only possible with a hypothetical full spectrum sensor), how would you store it? The second you convert it to RGB data it needs a perceptual conversion to the bit depth of the data format. Now even if you have a file format that can efficiently represent this, you'd also need full spectrum displays so that we could beam that exact color to your retinas.
Color science is incredibly complex. You're trying to trivialize it into matching your own narrow perception of color.
And also introduced me to the word "ontogenically". Thanks twice.
For example you might want to go to a beach or a park and shoot throughout the day on a bright day. Put people or objects in the foreground and then shoot them with either the light behind you or in front. Use the incident metering dome to meter the light
(you'll need to look this up, but the broad point of it is you stand in the same light as your subject and point the meter into the light, rather than at your subject)
Once you see what transparency film does in high-contrast situations I think you'll better understand what I'm trying to get across.
The dynamic range is clearly there. And we're not talking about such ridiculous values that the sensor noise becomes prominent.
You can do that correction in that situation because you've looked at the image, you know what it is meant to be, and you can decide on a set of adjustments that produce something that approximates what you want, perceptually.
But without truly extensive scene knowledge, cameras can't do that automatically, and they also can't know what information that is important to the photographer that they'd be affecting if they did.
Cameras have to try to ascertain what would be middle grey in a scene and then apply a general purpose tone curve to an image, but they do not know what is in the scene.
They can't even know for sure if the photo they are being asked to take is properly exposed by any absolute definition, in fact.
[I cut out a lot of this because I don't think it's going to be easy to complete the explanation here]
Have you ever shot photographs with a colour transparency film?
Gamma is just a single element of a color space. The whole trivializing sRGB into being a 2.2 Gamma versus linear is an over simplification that ignores gamut , white point, bit depth and more.
That's my point. You're trivializing what color is because you clearly have not dealt with it at scale.
You can download an alternate color scheme from Technicolor for Canon cameras that makes the colors appear fairly reasonable.
From what color space to what color space, and what display or print type?
Now you're back to describing a average case perceptual color rather than your initial point of accuracy.
https://xkcd.com/386/
Say that your eye is sensitive from light intensity 0 to 100 in some units, but your camera sensor only handles 40 to 60. That means that everything under 40 will be mapped to black, and everything above 60 will be mapped to white.
Only the picture file format should limit what range you can save with any modern camera.
In real life, photographs are printed on paper. The brightness of light reflecting off paper depends not only on the colour of the paper, but on the brightness of the illumination. (Likewise, photographs displayed on a computer monitor depend on the screen's brightness.)
In real life, human brightness perception depends on the brightness of the environment. An LED can look bright in the dark and dim in sunlight, and range dim to medium to bright on a cloudy day without anyone really noticing that the clouds between them and the sun are thicker or thinner.
In real life, there is no 0. There is no 100. Your comment doesn't make any sense.
The narrow band of sensitivity of a film or sensor has to be sort of moved to where it is needed (by controlling how much light gets in or for how long) according to the result the photographer is likely to want from their photo.
Even the most basic of film dead-reckoning methods -- Sunny 16 -- relies on subjective input from the photographer:
https://en.wikipedia.org/wiki/Sunny_16_rule
And it's up against the nature of human perception of light and dark, which as this classic page demonstrates, is complex:
https://scienceinfo.net/video-chessboard-illusion-confuses-p...
The main limitation isn’t the file format. The main limitation is the sensor. On the lower end, it is noise in different forms that overwhelm the very weak signal from dark areas. On the higher end, the sensors get saturated, that is, the semi-conductor bucket for the charges that is released by the photons get full.
And then the experience of the picture is of course limited by the medium that is used to display it. Even the best screens can’t show even a small fraction of the contrast that the eye experiences outdoors on a sunny day. And don’t mention printed media.
There's a fundamental problem with photography: a scene can contain up to 20 EV of dynamic range. Your camera can capture up to 14 EV. But your screen or a print can only depict 5-10 EV.
So something has to give. The camera capture is usually fine, only excluding the brightest highlights like the sun itself, and the darkest shadows, both of which we don't expect to contain detail anyway. But mapping the rest into the (let's say) 8 EV of available dynamic range of the screen is a problem.
Film does it in two ways: it rolls of highlights and shadows smoothly, preserving mid-tone contrast while compressing (and desaturating) extreme tones. Secondly, chemical diffusion enhances local contrast, while reducing global contrast, a bit like the "clarity" slider in Lightroom.
Smart phone cameras do something similar, with HDR image fusion, local contrast, and tone mapping.
Which is why, ultimately, only an edited picture can represent the experience of viewing a natural scene. The full tonal range of the scene can not be displayed. We have to rely on a somewhat artificial compressed rendition instead. But that's not a fault of the camera, or even the screen. But simply the result of showing an emissive reality on an (assumed) reflective medium. To me, it's the same perceptual unreality as projecting a 3D scene onto a 2D medium.
To me, it's what makes photography (and visual arts in general) interesting. They don't show reality, but a depiction of reality. And in that crop, project, compress, lies interpretation and expression.
8bit sRGB can contain 11.6 f-stops of dynamic range, and it is no longer enough for modern screens. There must be a longstanding bug somewhere. It would not be the first time it happened. There was a chroma decoding bug in almost all DVD players. A very similar issue to this, antialiasing in CGI used to be calculated without gamma, until GPUs got fast enough to use it and I suppose that someone started looking into why it performs worse than expected.
For digital, the data directly from camera sensors almost always needs some correction, de-mosaicing or massaging to generate an image viewable on a screen. This requires the camera to make what ends up being an aesthetic decision on what the photo looks like. Detail isn’t just how bright or how dark, but also the available gradients in between. This means there are cases where the dynamic range is automatically expanded (instead of clipped) and contrast unnaturally increased in order to have a photo that isn’t just mud.
Ultimately, this means that technical considerations map directly to artistic ones, and there is no objectively correct image from sensor data. The idea that a ‘no filter’ picture conveys some kind of divine truth is a myth.
Your description of reciprocity failure is not quite right. The idea is that if you double the time the shutter is open and also decrease the aperture by one stop, you should not change the amount of light hitting the film (you will change other things, of course). The overall brightness should be the same when you make these “reciprocal” adjustments. This does in fact hold pretty well within a certain range of shutter speeds. Reciprocity failure occurs at longer or smaller speeds, where the reciprocal relationship doesn’t quite work.
Each rgb channel is a filtered spectrum. But note that the color filters are essentially arbitrary, and only roughly correspond to the color filters of your eyes or your screen.
Also note that some cameras pre-process even raw data, for example with vignetting correction or noise reduction. Some phones even do image fusion and color correction, then re-rawify the data by mosaicing and linearization.
It's a game of fitting the captured scene with e.g. 11 stops of dynamic range to an output medium that has maybe 5 or 6 stops of dynamic range in order to trick human eyes with closer to 20 stops of dynamic range into believing what it sees on the print is "real/plausible". That is of course a very subjective process that involves a lot of choices regarding how to shape your curves and compress the available data.
Additionally, human brains do "funny" things with colors and actually re-construct/imagine things that aren't there. Getting the white balance and color grading "right" is another set of steps and what is right depends both on the conditions under which you capture the scene as under which conditions you view the end result.
Most phone cameras and in camera processing software algorithms for all of this that produce a certain look that is pleasing under most circumstances. But those are basically just a hard coded interpretation of the raw data. The point of post processing is having finer control over that process and the ability to use more expensive/better algorithms.
The worst trend being loud music and mumbled dialogue that make it impossible to experience even as a radio drama.
As an examples, I was watching the show '1883' and half the time I cannot understand the dialog!
Now I have the most expensive best new Sony 65" you can buy, so I'd expect the sound to be at least half decent. So it's not my out-of-the-box speakers.
I feel like I'm constantly having to turn the TV up!
Some Googling had people on forums suggesting it's 'muddy mixing' whatever that is, and that shows are now mixed for Surround Sound.
However when I watch a 'normal' TV show like South Park or an average British SitCom, I can understand every word.
The situations is bonkers and its turning me off even bothering to try and watch some shows!