How To Measure : Average Signal with Light Input

 

I know it has been a long time since the last technical blog.  As I earlier mentioned, at this time I do have one major problem : TIME !  But I have upgraded my software tools, and here we go again for the first measurement of the sensor with light input.  

Actually, what is the average signal of a sensor or a camera with light input ?  By definition it is the output of the image sensor or the camera when the light sensitive surface of the sensor is exposed to light.  This seems to be very straight forward, but if the measurement data is going to be used to measure for instance the FPN, the uniformity of the light source is very important !  Do not underestimate this item.  

On the other hand, the average light signal delivered by a sensor or a camera will be composed out of :

       A fixed DC offset, very often introduced by the analog circuitry on pixel-, on column- and on chip-level, or by an extra black level offset,

       A photon-generated part, which has a linear dependency on the exposure or integration time as well (at least if saturation of the sensor is not reached, and if a linear pixel is used),

The simplest way to separate the DC offset from the photo-generated part is to perform measurements at several exposure or integration times.   These measurements can be done by means of :

       A good old oscilloscope : in this way one can measure the average output voltage of a sensor or camera.  This method requires a uniform illumination of the sensor.

       The measurement of the reset-drain current, also based on an uniform illumination of the sensor.  This technique is only applicable if the drain(s) of the reset transistor(s) is/are available through a separate connection.  This is the case for CCD imagers, normally this is not the case for CMOS imagers.  So CCDs do offer a very easy way of measuring the average output signal, just by measuring the average reset drain current.  The relation between the measured reset drain current IRD and the average number of electrons in one pixel Npix is given in an earlier blog and will not be repeated here.

       Grabbing images by means of a frame-grabber and a computer.  Once the data of the images is present in the computer, calculation of the average signal becomes very simple.

Figure 1 shows the outcome of an average signal measurement with a uniform and constant  light source : at various exposure times and at 30 oC, multiple images are being grabbed, e.g. 25.  At each exposure time all these images were averaged (to reduce the thermal noise) and the averaged image is again averaged over all its pixels (to reduce the fixed-pattern noise).  The amount of light on the sensor is 5 lux, the spectrum has a colour temperature of 5600K and an near-IR filter HOYA500 is included.  In this measurement a sensor with 320 x 240 pixels is evaluated.  So every dot in Figure 1 is the result of 320 x 240 x 25 = 1,920,000 pixels.

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Figure 1 : average sensor signal as a function of the exposure time, measured at 30 oC.

Figure 1 contains 4 different signals, each representing one of the 4 colour channels : red, green (in the red line), green (in the blue line) and blue.  From the regression lines for the linear parts of the 4 curves, the following numbers can be deduced :

       Offset, independent of the exposure time and in principle also independent of the colour channel, being equal to 819 DN,

       Time depending part of the output signal, representing the photo-generated signal plus the dark current, and equal to 7613 DN/s for the red channel, 12715 DN/s for the green in red lines, 12653 DN/s for the green in the blue line and 8770 DN/s for the blue channel.

 “There is a warning sign on the road ahead” :

       It is clear that the average signal is depending on the exposure time, so accurately measuring or defining this parameter is very important,

       At this moment in the discussion, there is not yet any interest in the temporal noise behaviour of the sensor or camera.  To limit the influence of the temporal noise on the measurements it is recommended to take many images at every exposure time and averaged them on pixel level.  In this way the temporal noise will be averaged out,

       Notice that the measurement is done on the average signal with light input, but at very low light levels, the measurement may be influenced by the dark signal generation.  For that reason it is wise to use quite a bit of light to avoid that the dark signal is “contaminating” the measurement.  A rule of thumb : at every particular exposure time, the signal generated by means of the light on the sensor should be a factor of 100 times larger than the dark signal at that particular exposure time,

       The average signal will change from pixel to pixel (see one of the next blogs) and can also be influenced by a shading component (slowly varying from one side of the sensor to the other side of the sensor).  Non-uniformities and shading are both included in the average output of the sensor on dark.  Or, the average dark signal does not tell anything about the uniformity of it !  To avoid the effect of shading, the sensor signal of a small area (preferably in the center of the sensor) can be evaluated,

       The light sensitivity of the pixels can strongly depend on the angle of incidence.  The sensor response is the largest for perpendicular incoming rays.  For that reason it is advisable to use collimated light input,

       It may sound as a very straightforward requirement, but it is of absolute critical importance that the light source is stable (colour temperature and intensity).  You will not be the first one who is using a AC-powered light source ….

       The measurement presented in this blog is using a colour imager, but it should be clear and straightforward that the same methodology can be used on a monochrome device as well.

Next time the photo-response non-uniformity or PRNU will be discussed.

Albert, 30-01-2012.

 

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