Construct · 3 fields · 3 citations

dynamic range: one construct, many systems

One name. One construct. Different systems. One map.

● invariant · one construct, three systems Nearest construct by meaning·not indexed
same ratio, in soundthe range a system can code at alldynamicrange3 SYSTEMSScene dynamic rangeDEBEVEC & MALIK · 1997Audio dynamic rangeRUMSEY & McCORMICKNeural dynamic rangeKINOUCHI & COPELLI · 2006

Spokes are the systems the one construct recurs in; dashed arcs are shared lineage. Tap a field for its definition, unit, and measures.

1997Scene dynamic range2006Neural dynamic range2009Audio dynamic range
2026

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Imaging / photography

Brightest to darkest a sensor can hold

In imaging, dynamic range is the ratio between the brightest and darkest scene luminances a film or sensor can record together without clipping to white or crushing to black, usually expressed in stops or decades of light. Debevec and Malik's 1997 Recovering high dynamic range radiance maps from photographs showed how to recover a scene's full range by combining differently exposed frames, the basis of high-dynamic-range imaging. The referent is the span of signal an imaging system faithfully captures between its noise floor and its saturation point, measured in stops, and it is the same ratio-of-extremes construct that recurs in audio and in sensory coding.[1]

Unit
The ratio of the largest to the smallest recordable light signal, in stops
Recovery means
Not applicable
Measured by
Measured as the ratio of saturation exposure to the noise floor, reported in stops or decibels

Audio engineering

Loudest to quietest without distortion or hiss

In audio engineering, dynamic range is the ratio between the loudest signal a system can pass without distortion and the quiet noise floor beneath which signal is lost, reported in decibels. Rumsey and McCormick's Sound and recording treats how recording chains, converters, and media set this span and how it limits what a track can hold. It is the identical ratio-of-extremes construct as an imaging sensor's range, realised in sound and measured against distortion and hiss rather than clipping and shadow noise.[2]

Unit
The ratio of the loudest undistorted signal to the noise floor, in decibels
Recovery means
Not applicable
Measured by
Measured as the decibel difference between maximum undistorted level and the residual noise floor

Neuroscience / complex systems

The span of stimuli a network can tell apart

In sensory neuroscience, dynamic range is the span of stimulus intensities a system can distinguish by its response, from the weakest it reliably detects to the point where response saturates, again a ratio of extremes. Kinouchi and Copelli's 2006 Optimal dynamical range of excitable networks at criticality showed that a network of excitable units maximises this range precisely at a critical point, linking the engineering quantity to how neural tissue codes intensity. It is the same construct as a camera's or an amplifier's dynamic range, transposed to the range of inputs a coding system can represent at all.[3]

Unit
The ratio of the strongest to the weakest distinguishable stimulus a network codes
Recovery means
Not applicable
Measured by
Read from the response-versus-stimulus curve as the intensity ratio between near-threshold and near-saturation response

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Nearby constructs

noise floor1 fields · 2 citationsanchor · a standalone construct in electroacousticsbasis3 fields · 5 citationsjingle · one word, three constructsbracketing1 fields · 1 citationsanchor · a standalone constructhigh dynamic range imaging1 fields · 1 citationsanchor · a standalone construct

References

  1. Debevec, P. E., & Malik, J. (1997). Recovering high dynamic range radiance maps from photographs. In Proceedings of the 24th annual conference on computer graphics and interactive techniques (SIGGRAPH '97) (pp. 369–378). ACM Press. https://doi.org/10.1145/258734.258884
  2. Rumsey, F., & McCormick, T. (2009). Sound and recording (6th ed.). Focal Press. ISBN 9780240521633
  3. Kinouchi, O., & Copelli, M. (2006). Optimal dynamical range of excitable networks at criticality. Nature Physics, 2(5), 348–351. https://doi.org/10.1038/nphys289

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