Comment by dljsjr | Hacker News Reader

Comment by dljsjr | Hacker News Reader

> According to Wikipedia, “Dither is an intentionally applied form of noise used to randomize quantization error”, and is a technique not only limited to images. It is actually a technique used to this day on audio recordings […]

Dithering as a digital signal processing technique is also used frequently in the digital control of physical systems. One example of this is in the control of hydraulic servo valves[1]; these valves are usually pretty small and their performance can be dominated by a lot of external factors. One of the biggest ones is "stiction", or static friction, wherein if the moving parts of the valve are at rest it can take a large amount of current to get them going again which translates in to poor control of the valve and in turn poor control of the thing the valve is trying to move. It's common to use very high frequency/small amplitude dithering on these valves to eliminate the effects of stiction without compromising accuracy which greatly improves the control stability and responsiveness of the servo valves.

1: https://en.wikipedia.org/wiki/Electrohydraulic_servo_valve

I would not define it exactly like that. I would say "Dithering is any method of reducing the bit depth of a signal that prioritizes accurate representation of low frequencies over that of high frequencies". This frames it as essentially an optimization problem, with randomn noise being a heuristic way of accomplishing it.

I feel like that is still a very narrow definition. Dithering's useful anywhere quantization produces an unwanted result, and is useful in a lot of places where "bitrate" isn't even a concept

Good image dithering algorithms do maintain sharp features like edges.

I think the best way of thinking about dithering, is that it's the 'whitening' of quantization noise. Quantization can be modelled by taking the difference between the originally continuous signal, and the resultant quantized image as "quantization noise". The resultant noise has a spectrum that's pretty 'spiky' due to its non-continuous nature, it has significant energy in its higher-frequency harmonics. By adding some noise before sending it off to be thresholded by the quantizer, the noise's spectrum is made a lot flatter, thus making the quantized image look more like the original image, but with a higher noise floor.

I worked with a team that included printing, low-level graphics rendering. When we were able to rename our lab at work we went with "Dithering Heights."

I believe this is what the engines are doing during the majority of the ascent of the Starship SN8 test vehicle[0]. You can see the engines gimbaling very slightly in a circular pattern.

[0]: https://youtu.be/ap-BkkrRg-o?t=6516

Anything controlled by a PID can easily end up in a circular pattern, so it's not a given that this was to avoid stiction.

[edit]

1 dimensional PIDs can end up in a sinusoidal dynamic equilibrium, and a 2 dimensional sine wave is an ellipse.

It's not an ellipse if the axes have different periods: https://www.wolframalpha.com/input/?i=x%3Dsin%28t%29%2C+y%3D...

(Is there a name for this kind of curve?)

PWM signals are dithered by definition, and are probably the most common interface, no?

Servo valve dithering is overlaid on top of the PWM duty cycle.

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