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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.
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)
https://en.wikipedia.org/wiki/...
https://ccrma.stanford.edu/~jo...
https://www.dsprelated.com/fre...
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