How is a camera sensor’s spectral sensitivity measured and expressed?

Asked 9/27/2017

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I’m trying to understand how to derive a camera sensor’s spectral response/sensitivity curve for each color channel. I know this is typically measured with monochromatic light (for example from a monochromator or spectrometer) and calibrated exposures, but I’m unclear on what is actually calculated from the images.

When I see published graphs, the x-axis is wavelength and the y-axis is just “spectral response” with no obvious units. Are these curves usually just normalized pixel values at each wavelength, or are they expressed in physical units such as quantum efficiency or output signal per irradiance?

More broadly, what is the usual workflow for going from a set of monochromatic captures to per-channel spectral sensitivity curves? My end goal is to use a camera’s spectral sensitivity together with animal photoreceptor response data to build a vision model.

Originally by Photography Stack Exchange contributor. Source · Licensed CC BY-SA 4.0

Photography Stack Exchange contributor

8y ago

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There are two ways to express the wavelength dependent sensor responsivity in the context of a system analysis.

First, it can be expressed as a percentage. This can be a peak normalization, in which case the highest value will be 1.0. More commonly, the percentage is expressed in units of quantum efficiency. For most consumer cameras this will average about 30-40% but specialized BS-CMOS sensors could hit 85% without a bayer filter.

Secondly, the value used to express responsivity is the sensor response value. This is either digital count or output voltage at some point in the sensor circuit before the ADC. The value is the numerator in the responsivity ratio where the denominator is watts per meter^2. It is common practice, however, to set the demoninator equal to 1 E.G. one would say 500 digital count per wm^2 rather than 2000 digital count per every 4 w/m^2.

The advantage of the latter value is that the digital count response can be directly calculated from the irradiance. One need only account for loss of light to the lens assembly and, if present, the microlens array. This can generally be done as "mental math." Converting relative or absolute quantum efficiency to digital counts, on the other hand, requires that the digital response be calculated via plank's constant and the sensor quantization formula.

Originally by user71671. Source · Licensed CC BY-SA 4.0

user71671

8y ago

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Yes—at a basic level, you illuminate the sensor with known narrow-band light at many wavelengths, record each channel’s response, and plot response versus wavelength.

The y-axis can be shown in a few common ways:

  • normalized response (unitless, often peak set to 1)
  • quantum efficiency (percent of photons converted to signal)
  • electrical/digital response per incident irradiance or radiant power

That’s why many published curves appear unitless: they are often normalized to compare shape rather than absolute sensitivity.

In practice, you would sample the pixel values from calibrated monochromatic captures for each channel, subtract dark/black level, keep exposure and illumination known, and then either:

  • normalize the resulting values to get relative spectral sensitivity curves, or
  • divide by the known incident light level to get an absolute responsivity curve.

If your goal is color/vision modeling, the normalized per-channel spectral sensitivity is often the key quantity, provided the measurement conditions are controlled and the optical path (filters, CFA, sensor stack) is included consistently. Absolute units matter more if you need true radiometric response, not just spectral shape.

So the short answer is: yes, the curves can come from measured pixel values, but whether they are unitless or physical depends on whether you normalize them or calibrate them against known input energy.

UniqueBot

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8y ago

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