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A New Sampling Algorithm Could Eliminate Sensor Saturation (scitechdaily.com)
Baron_Yam shared an article from Science Daily:
Researchers from MIT and the Technical University of Munich have developed a new technique that could lead to cameras that can handle light of any intensity, and audio that doesn't skip or pop. Virtually any modern information-capture device -- such as a camera, audio recorder, or telephone -- has an analog-to-digital converter in it, a circuit that converts the fluctuating voltages of analog signals into strings of ones and zeroes. Almost all commercial analog-to-digital converters (ADCs), however, have voltage limits. If an incoming signal exceeds that limit, the ADC either cuts it off or flatlines at the maximum voltage. This phenomenon is familiar as the pops and skips of a "clipped" audio signal or as "saturation" in digital images -- when, for instance, a sky that looks blue to the naked eye shows up on-camera as a sheet of white.
Last week, at the International Conference on Sampling Theory and Applications, researchers from MIT and the Technical University of Munich presented a technique that they call unlimited sampling, which can accurately digitize signals whose voltage peaks are far beyond an ADC's voltage limit. The consequence could be cameras that capture all the gradations of color visible to the human eye, audio that doesn't skip, and medical and environmental sensors that can handle both long periods of low activity and the sudden signal spikes that are often the events of interest.
One of the paper's author's explains that "The idea is very simple. If you have a number that is too big to store in your computer memory, you can take the modulo of the number."
Last week, at the International Conference on Sampling Theory and Applications, researchers from MIT and the Technical University of Munich presented a technique that they call unlimited sampling, which can accurately digitize signals whose voltage peaks are far beyond an ADC's voltage limit. The consequence could be cameras that capture all the gradations of color visible to the human eye, audio that doesn't skip, and medical and environmental sensors that can handle both long periods of low activity and the sudden signal spikes that are often the events of interest.
One of the paper's author's explains that "The idea is very simple. If you have a number that is too big to store in your computer memory, you can take the modulo of the number."
1. Audio clipping is present in purely analog recording systems (an playback) so not an ADC problem.
2. The sensor, any sensor, has physical limits, that will cause saturation (i.e. clipping) regardless of the cleverness of the ADC downstream.
3. In most cases it is easier to devise an ADC with enough bits (i.e. precision and dyanmic range) large than the sensorr it is connected to
Summary: a solution in search of a problem.
No, it's not normalization. From a preliminary reading, they're just doing rudimentary frequency analysis to provide qualifications under which modular representations can be inversely mapped to a real world Voltage reading, i.e. a low-enough-energy high frequency component such that an extremely high to extremely low (or vice-versa) transition can be interpreted unambiguously as bounds clipping rather than a transition within the typical dynamic range of the device. That's why they're taking the sampling theory approach.
Nothing mind-blowing, I agree, and the headline is definitely hyperbolic, but if you're gonna talk shit you should get your shit straight first.
It's a different type of ADC, one that resets when it reaches saturation. So you can forget about using this 'new algorithm' in your existing equipment.
Their paper seems to ignore that this technique isomorphic to the well known phase unwrapping problem. The hard part has always been implementing it at the pixel level. This requires extra transistors, calibrations (because every pixel needs to be the same) and perfect uniformity in manufacturing, as well as a new source of noise. Finally the mathematical problem produces nasty noise unless you can also implement hystersis at the point of the amplitude wrap. If you don't it's going to suck, and if you do then you have even more transistors to implement for each pixel since it's now having to be stateful (know it's earlier state to implement the hysteresis)
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This is an interesting approach, and it would work pretty well for things like audio. It might help with the dynamic range of cameras when used at higher ISO settings, but it will not solve the problem by any means. The problem, though, is that in modern cameras, the sensor's pixels also have a maximum capacity, called the full well capacity. The sensor can't physically accumulate more of a charge than its full well capacity, and the DAC is designed so that its clipping point matches the full well capacity of the sensor at its base ISO. So you would still get clipping when the brightness exceeds what would otherwise by the sensor's clipping point at its base ISO, and if it is already at its base ISO, this wouldn't make any difference at all.
IMO, a better approach (which I proposed several years ago) is to sample the sensor and physically cancel out (subtract) the measured charge in the sensor itself, doing this multiple times per exposure to ensure that you don't hit the full well capacity. That approach also has the advantage of letting you do really cool time-based manipulation of the resulting photo. For example, you could do vector-based motion compensation of the individual subframes to dramatically reduce motion blur, compensate for some amount of camera shake, etc.
Even better, if you represent subsequent subframes relative to the previous subframe (e.g. -12 here, +2 there), you'll also usually get a high percentage of zeroes, which means you should be able to losslessly compress the additional subframes to be pretty small on average, potentially giving you the ability to adjust the image motion compensation after the fact to get an image in which motion is blurred more or less, according to taste.
In theory, you could even do bizarre, per-region motion compensation, such as making a baseball appear to be motionless while the bat is swinging at a high speed or vice versa. :-D But I digress.
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I think you meant to be funny, but it is possible to come full circle on this one.
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Good audio converters are 24 bit these days.
That means you can have 20bits worth of dynamic range (~120dB) with 4 bits worth of clipping headroom (24dB).
That will exceed whatever is plugged into the A/D.
High end cameras are using 14bit converters (uber high end has hit 16), so the problem is pretty much solved there too.
Nothing mind-blowing
Go back and do more than a preliminary reading. They are utilizing a property of a specific type of ADC (a so-called set-reset ADC or SR-ADC), which instead of saturating reverts to the lower bound value when the input voltage exceeds the upper bound, and vice versa.
I admit that I don't understand their algorithm, however they were able to reconstruct a random signal with a maximum amplitude exceeding 20 times the ADC upper bound. The mean squared error between the original and constructed signals was 1.5 x 10^-33.
Maybe it's just me, but I think that's pretty mind blowing.
Only crack the nuts that crack. You don't put the ones that don't crack in the sack.
I've skip read the Paper and /. comments, and this reads like mathematical wank by guys that have never touched an oscilloscope.
First, they are waving their hands in the are about a magic 'resetting ADC'... seriously...
Do they even know what reset means? It has to be performed at the hardware level, It has to performed with DC offsetting (from a D/A converter), it has to be performed to 1 least significant bit of accuracy, and the input signal has to be rate limited. No way this will happen for any practical systems without adding artefacts when the offsetting circuitry tries to slew the input within one sample period.
The only real world way I can think of, that still retains DC accuracy, is servoing the input.
This is where a 'counteracting' force is used to subtract from the input... but servoing has hairs all over it, as it has to be super accurate in terms of amplitude and frequency response.
They should have talked to an electrical engineer before spouting off this rubbish.
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I'm an EE. This concept is interesting to me, but then I'm left wondering how they really tackle the problem of signal limits. It's not just that ADC that limits the signal. The amplifiers in the chain also do it. Maybe I should just read about it. The whole self-resetting ADC concept just strikes me as odd. I have a feeling it was invented to improve the dynamic range or sampling rate or reduce the power usage of ADCs, but not to magically sample arbitrarily large signals.
pure analong systems have been doing this for decades, let's bring back the vacuum tube
You could have just said "I didn't read the article". It would have been shorter to write.
They can design any ADC they want. A saturated transducer will be saturated regardless. No need to read the paper. GIGO ... It isn't just for software.
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No, it's not quite the same thing, although the concepts are related. In this case, reconstructing your signal is still limited by the Nyqvist frequency of course, but your ability to reconstruct across the ADC reset discontinuities also requires that the amplitude doesn't change so fast that you get more than one wrap per sample period.
I suspect it actually is the Nyqvist limit, but applied in this weird phase, er, amplitude unwrapping situation.
What I wonder is, say you have a 5V ADC. Using their technique, could you drive a 15V (max) signal into the ADC and effectively triple your resolution? You're still using all your bits to measure a 5V range... so if that's the case then it truly is quite groundbreaking.
It may be groundbreaking, but not for the reason advertised in the paper/article/summary. From a quick look at this paper, ADC power dissipation is proportional to f * 2^(2*n), where f is the sampling rate and n is the number of bits per sample. High performance ADCs are constrained by power dissipation, which limits either sampling rate or resolution. What these guys are probably trying to do is constrain n. By allowing signals larger than the ADC input range, and then unwrapping them in software, they increase the effective number of bits. Even if they gain only 2 bits by doing this, this is a factor of 16 advantage in power dissipation (but how does the self-resetting ADC compare to normal ADCs in terms of power?). In any case, the article seems to be hyping a non-existent advantage (sampling signals exceeding the nominal ADC range - why not just attenuate the signal and use a higher resolution ADC?), but does not mention the real advantage (power dissipation).
"So what you are claiming is that you had pure analogue, analogue to digital converters?"
"Replacing silicon transistors with valves does not change the fact that the circuit is still digital."
All circuits are analog. Period. That's the physics of it. 'Digital' is just a sampled section of the signal measured against a reference voltage. Those are still both analog waveforms or sections thereof.
It's like people suddenly forgot the bare fucking basics and physics of basic electronics when the world went digital. You dipshits fell hook line and sinker for the digital marketing hype.
Still waiting on Serviscope_minor to wake up to fucking reality and realize that Jessica Price isn't going to fuck him.
All circuits are analog. Period. That's the physics of it.
If you are going to get that pedantic then no you are wrong in two ways. First go look up quantum mechanics and then know that this governs how semi-conductors work. These devices transition between two, binary states in a non-analogue way smeared out a little by thermal effects. However, the end result of this is that they allow a certain amount of charge to pass which is either above some threshold or not and so we treat it as a one or zero.
Hence the circuit is digital because we define our own, artificial thresholds to quantize how we treat the result. This is what makes it digital. If you also happen to be using semiconductors then it is also quantized at a more fundamental level by the physics in the semiconductor...and these quantum effects get increasingly important as we shrink the size of circuits.
Oh you mean they turned the dial to 11 ?