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> Shouldn’t the image taken at ISO 6400 show more noise than the image taken at ISO 1600? If the exposures were the same brightness, yes. But these images were

> Shouldn’t the image taken at ISO 6400 show more noise than the image taken at ISO 1600? If the exposures were the same brightness, yes. But these images were not taken with the same exposure. The first image started with twice as much shutter open time (30 seconds versus 15 seconds) and two stops more gain on the sensor (ISO 6400 vs ISO 1600). The result is that the first image has significantly more light data. This makes the final signal-to-noise ratio of the processed images higher on the first image. The higher the signal to noise ratio, the less noisy the resulting photo. So in this case it was actually better to overexpose and compensate later in post processing, despite the initial unprocessed images appearing unusable. This is really neat. I've got a full frame camera with a sensor that has very good dynamic range and I'd learned to under-expose and then pull detail from the shadows in post processing as information can't be saved from blown highlights. This sort of flips that on its head, except the featured overexposed shot didn't have blown highlights, it just looked like it did. Instead it had a wealth of low-light data.

kinkrtyavimoodh 9y ago
That is the right technique in general when overexposing would clip highlights. Here's that's not really a risk, so the other direction works better.
hopfenspergerj 9y ago
ETTR is a real technique to maximize SNR. Underexposing and then boosting shadows is just a good way to guarantee that your image has no contrast, and comes out looking flat and grey all over.
michrassena 9y ago
What I've learned over the years with digital cameras -- you can't trust the preview image. The histogram tells much more of the story (if not the whole truth). My photographs have become much better (in a technical sense) after I learned to expose almost to the point of blowing highlights, making sure there is little blank space at the right (where the highlights are displayed) of the histogram as possible (hence the term Expose To The Right). As someone downthread stated, this improves the signal-to-noise ratio of the captured data. There's an unwritten assumption that the camera's built-in auto-exposure capability isn't sophisticated enough to expose the scene properly, and the photographer has to take control. This is often the case. And speaking of SNR, there are a few tricks astro-photographers have been using for years that occasionally find their way into mainstream photography. One is image stacking, where you combine multiple photographs of the same scene (useful for landscapes if a little blur isn't a problem for you) into a single image. This pushes the shot noise (the random distribution of noise) down even further. I've gotten clean images out of cheap cameras, and even from cheap cell phone cameras (given enough images). The other technique is dark frame subtraction, where you take an photo with the lens covered at the same ISO/shutter/aperture as the rest of the set. Digital sensors have readout noise and heat noise which tends to be very predicable. Subtracting this noise gives you a cleaner shot as well. On a side note, I do wish when talking about ETTR and even digital photography in general that the term "overexpose" wasn't used when explaining the technique of overriding the cameras default metering with exposure compensation. Overexposure would be blowing the highlights, or at least the highlights of details that the photographer considers important (e.g. blowing the highlights of street lights is usually okay). The "over" portion makes it sound like the photographer is doing too much of something, when in reality ETTR is a technique of giving enough exposure, but not too much.
- vanderZwan 9y ago
  > One is image stacking Since you seem to have experimented with this, I'd like to ask: don't you need a certain "minimum" time to capture the faintest of stars, because their signal otherwise wouldn't rise above the noise floor? I've been curious about this with stacking in atrophotography for a while. > The other technique is dark frame subtraction, where you take an photo with the lens covered at the same ISO/shutter/aperture as the rest of the set. Digital sensors have readout noise and heat noise which tends to be very predicable. Subtracting this noise gives you a cleaner shot as well. For long exposures this heat noise becomes more problematic: long exposures heat up the sensor quite a bit. Have you tried building your own customised electric coolbox to keep temperatures down? It can be a fun project! I actually used this in a different context: during long Skype sessions at home with my people abroad, my phone heats up a lot and the video would start stutter. Putting it on a cooling block actually fixes that. This had more to do with the system not having to scale back CPU performance to let the phone cool down, but a side-effect according to people on the other end of the line, was that the image quality improved too
  - jxcl 9y ago
    > don't you need a certain "minimum" time to capture the faintest of stars, because their signal otherwise wouldn't rise above the noise floor? I'm not an expert or even very knowledgeable on image stacking, but I'll share my experience. I've taken a stacked picture of the Orion constellation. 15 exposures at 5 seconds each, and combined them to get this photo: https://www.flickr.com/photos/abliskovsky/31756623694/ https://www.flickr.com/photos/abliskovsky/31756623694/ In none of the individual exposures is the Orion Nebula visible, but in this photo it's pretty clear. So in the end I'm fairly sure that your statement is true, but the signal required is very, very faint.
    - craftyguy 9y ago
      Do you know of any good resources for "getting into" image stacking for a complete newbie? 2 years ago I tried stacking images I took of Jupiter in my 16" dob (taken with a Canon DSLR), but it was terrible and I'm not confident I used the app I found (I think it was AstroStack..) for image stacking correctly.
vanderZwan 9y ago
What article doesn't explain is the physics behind why ETTR captures more light data: our perception of light scales logarithmically, while a CCD captures it linearly. Each stop is a doubling (or halving) of the amount of light captured. CCDs work by increased voltage based on captured photons. Imagine back to when digital photography just started, when we were stuck with 10-bit RAW images (before processing them to 8 bit JPGs). That's 1024 different values per channel, not a whole lot of room to begin with. Because we're converting a linear signal to a logarithmic one, that means that highest stop in the image takes up 512 of those values. EDIT: As rightfully pointed out in a reply, 8-bit JPGs are not in linear colour space any more - so this logic does not apply there (however, JPG compression is more harsh on shadow details, since it's lossy, and it tries to move that loss of information to the parts of the image where you're less likely to notice, like the shadows, but we're digressing) By that logic, the low light data should have a lot more banding than the highly exposed data. Try it with level tools on a RAW file and see for yourself. So you can imagine that when the dynamic range of (part of) the scene that you want to capture is less than the dynamic range of your sensor, you want to be on the right edge of the histogram (all else being equal - if this causes motion blur due to long exposure it's pretty useless) Caveat: this is potentially outdated knowledge, perhaps the analog/digital converter in modern cameras actually converts the voltage of a CCD to a (pseudo)logarithmic scale for the digital output, which might partially circumvent this issue (although the sensor is still linear). And nowadays many of the better cameras have 14-bit A/D converters - the usefulness of which also largely depends on the quality of the sensor - so there's a lot more detail in the shadows than before.
- sosuke 9y ago
  You should write an article on the subject. Seems there are a lot of interested people in the process and you've got some domain specific knowledge to lay it out nicely.
  - daviesgeek 9y ago
    I agree. I’d love to read an article about this!
  - 9y ago
devb 9y ago
I'd rather see a comparison between two 30-second exposures at 1600 and 6400 than what was presented here. That would give a much better idea of how much detail you're losing from sensor gain.
Obi_Juan_Kenobi 9y ago
If the scene has a lot of variation in brightness, then I'll always opt to save the highlights over the shadows. Shadow detail recovers remarkably well, while clipped highlights are ghastly.

kinkrtyavimoodh 9y ago

That is the right technique in general when overexposing would clip highlights. Here's that's not really a risk, so the other direction works better.

hopfenspergerj 9y ago

ETTR is a real technique to maximize SNR. Underexposing and then boosting shadows is just a good way to guarantee that your image has no contrast, and comes out looking flat and grey all over.

michrassena 9y ago

What I've learned over the years with digital cameras -- you can't trust the preview image. The histogram tells much more of the story (if not the whole truth). My photographs have become much better (in a technical sense) after I learned to expose almost to the point of blowing highlights, making sure there is little blank space at the right (where the highlights are displayed) of the histogram as possible (hence the term Expose To The Right). As someone downthread stated, this improves the signal-to-noise ratio of the captured data. There's an unwritten assumption that the camera's built-in auto-exposure capability isn't sophisticated enough to expose the scene properly, and the photographer has to take control. This is often the case. And speaking of SNR, there are a few tricks astro-photographers have been using for years that occasionally find their way into mainstream photography. One is image stacking, where you combine multiple photographs of the same scene (useful for landscapes if a little blur isn't a problem for you) into a single image. This pushes the shot noise (the random distribution of noise) down even further. I've gotten clean images out of cheap cameras, and even from cheap cell phone cameras (given enough images). The other technique is dark frame subtraction, where you take an photo with the lens covered at the same ISO/shutter/aperture as the rest of the set. Digital sensors have readout noise and heat noise which tends to be very predicable. Subtracting this noise gives you a cleaner shot as well. On a side note, I do wish when talking about ETTR and even digital photography in general that the term "overexpose" wasn't used when explaining the technique of overriding the cameras default metering with exposure compensation. Overexposure would be blowing the highlights, or at least the highlights of details that the photographer considers important (e.g. blowing the highlights of street lights is usually okay). The "over" portion makes it sound like the photographer is doing too much of something, when in reality ETTR is a technique of giving enough exposure, but not too much.

vanderZwan 9y ago
> One is image stacking Since you seem to have experimented with this, I'd like to ask: don't you need a certain "minimum" time to capture the faintest of stars, because their signal otherwise wouldn't rise above the noise floor? I've been curious about this with stacking in atrophotography for a while. > The other technique is dark frame subtraction, where you take an photo with the lens covered at the same ISO/shutter/aperture as the rest of the set. Digital sensors have readout noise and heat noise which tends to be very predicable. Subtracting this noise gives you a cleaner shot as well. For long exposures this heat noise becomes more problematic: long exposures heat up the sensor quite a bit. Have you tried building your own customised electric coolbox to keep temperatures down? It can be a fun project! I actually used this in a different context: during long Skype sessions at home with my people abroad, my phone heats up a lot and the video would start stutter. Putting it on a cooling block actually fixes that. This had more to do with the system not having to scale back CPU performance to let the phone cool down, but a side-effect according to people on the other end of the line, was that the image quality improved too
- jxcl 9y ago
  > don't you need a certain "minimum" time to capture the faintest of stars, because their signal otherwise wouldn't rise above the noise floor? I'm not an expert or even very knowledgeable on image stacking, but I'll share my experience. I've taken a stacked picture of the Orion constellation. 15 exposures at 5 seconds each, and combined them to get this photo: https://www.flickr.com/photos/abliskovsky/31756623694/ https://www.flickr.com/photos/abliskovsky/31756623694/ In none of the individual exposures is the Orion Nebula visible, but in this photo it's pretty clear. So in the end I'm fairly sure that your statement is true, but the signal required is very, very faint.
  - craftyguy 9y ago
    Do you know of any good resources for "getting into" image stacking for a complete newbie? 2 years ago I tried stacking images I took of Jupiter in my 16" dob (taken with a Canon DSLR), but it was terrible and I'm not confident I used the app I found (I think it was AstroStack..) for image stacking correctly.

vanderZwan 9y ago

What article doesn't explain is the physics behind why ETTR captures more light data: our perception of light scales logarithmically, while a CCD captures it linearly. Each stop is a doubling (or halving) of the amount of light captured. CCDs work by increased voltage based on captured photons. Imagine back to when digital photography just started, when we were stuck with 10-bit RAW images (before processing them to 8 bit JPGs). That's 1024 different values per channel, not a whole lot of room to begin with. Because we're converting a linear signal to a logarithmic one, that means that highest stop in the image takes up 512 of those values. EDIT: As rightfully pointed out in a reply, 8-bit JPGs are not in linear colour space any more - so this logic does not apply there (however, JPG compression is more harsh on shadow details, since it's lossy, and it tries to move that loss of information to the parts of the image where you're less likely to notice, like the shadows, but we're digressing) By that logic, the low light data should have a lot more banding than the highly exposed data. Try it with level tools on a RAW file and see for yourself. So you can imagine that when the dynamic range of (part of) the scene that you want to capture is less than the dynamic range of your sensor, you want to be on the right edge of the histogram (all else being equal - if this causes motion blur due to long exposure it's pretty useless) Caveat: this is potentially outdated knowledge, perhaps the analog/digital converter in modern cameras actually converts the voltage of a CCD to a (pseudo)logarithmic scale for the digital output, which might partially circumvent this issue (although the sensor is still linear). And nowadays many of the better cameras have 14-bit A/D converters - the usefulness of which also largely depends on the quality of the sensor - so there's a lot more detail in the shadows than before.

sosuke 9y ago
You should write an article on the subject. Seems there are a lot of interested people in the process and you've got some domain specific knowledge to lay it out nicely.
- daviesgeek 9y ago
  I agree. I’d love to read an article about this!
- 9y ago

devb 9y ago

I'd rather see a comparison between two 30-second exposures at 1600 and 6400 than what was presented here. That would give a much better idea of how much detail you're losing from sensor gain.

Obi_Juan_Kenobi 9y ago

If the scene has a lot of variation in brightness, then I'll always opt to save the highlights over the shadows. Shadow detail recovers remarkably well, while clipped highlights are ghastly.