Persons who want to understand why camera makers throw around terms like median and rms on readout noise specification
An explanation, with visuals
Learn more about noise and CMOS technology, read Changing the Game.
With any statistical parameter there are multiple models available to apply to the data. The classic electrical engineering method for calculating readout noise is to define the root mean square (rms). This has always been the method used to calculate readout noise for CCDs. Median and rms are both perfectly valid statistical models, but only rms noise accurately represents the experience that a user can expect from a camera. With CCDs there are never any issues regarding which model to use because the typical readout noise for all pixels is very similar, thus rms and median are equivalent. With sCMOS, the structure of the sensor inherently has more pixel variation, and the extreme low noise of the sensor makes variation more statistically significant. So when it comes to evaluating camera performance, the truly meaningful spec is rms noise. The rms noise value provides insight into image quality as well as being the appropriate noise variable in quantitative calculations. For example, SNR measurements made empirically align with theory only when these simulations are done using rms noise values. There is no industry standard in scientific imaging for reporting noise specifications, but we encourage users to be skeptical of median noise as a specification and to demand the more meaningful rms noise.
The median value shown is simply the point at which half the pixels have more read noise and the other half have less. Given the nature of noise distribution in sCMOS cameras it is not particularly informative. RMS is the root mean square value of the read noise across all pixels and offers meaningful insight into image quality with pixel correction OFF. It is the value best used in image SNR calculations.
RMS or median noise values are valid only if all the pixels in the sensor are used or if the exclusion of outlier pixels is documented and explained. For our scientific CMOS camera, we calculate the rms readout noise using every pixel in the sensor. This is done without any pixel correction functions or prequalification of the data. Since one goal of providing a spec is to enable accurate quantification of imaging results, this approach is consistent with our goal of providing the best quantitative scientific cameras.
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