Defining 'Dynamic Range' in a simple way

Started Oct 23, 2013 | Discussions thread
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boggis the cat Veteran Member • Posts: 6,329
Defining 'Dynamic Range' in a simple way

I started a thread asking about down-sampling and 'dynamic range', but have now decided that I really should have started with defining dynamic range. (Or collating different definitions in order to make sense of what is being discussed.)

Here is my take on a thought experiment to define 'dynamic range'.

Assume that we have the following:

  • A sensor that produces a 14-bit depth raw
  • A scene that has a perfectly black target (emits no light) -- for example, a black body located down a long black tube -- and a light source that can be set to an arbitrary brightness
  • All other considerations can be ignored ('perfect' lens, no camera movement relative to target, etc.)

If I take a photo of my scene, adjusting the exposure such that the light source falls right on the clipping limit, then the raw data should yield exactly 14 bits -- a value of 16383 (2^14 -1) for the brightest pixel.

Now, if the pixels that fall over the black target average out to a value of 127 (2^7 - 1) then the captured 'dynamic range' is 7 EV (14 - 7, assuming a linear A2D fit).  If the 'black' pixels average out to 63 (2^6 - 1), then the captured 'dynamic range' is 8 EV (14 - 6).

Given that there will be noise in every pixel (each data point), the perceived 'dynamic range' will be reduced.  If the black target area looks uniform then the noise is low and the perceived DR will be close to the theoretical calculated amount; and if the black target area looks very speckled then the noise is high and the perceived DR will be potentially considerably lower than the calculated DR.

Comments and criticisms of this scenario?  Is there a better way to simplify the 'real scene dynamic range to captured data dynamic range' process?


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