It may sound strange that an image sensor, which is made to capture light, will be characterized first in dark conditions. But actually this should not really be surprising because noise will first become visible in the darkest parts of an image. For that reason the dark performance of an image sensor plays crucial role. It also sets the lower end of the dynamic range.

In this course, the fixed-pattern noise (= correlated noise) will be measured first, next the temporal noise (= uncorrelated noise) will be characterized. All measurements will be done based on real images taken by a commercially available camera. For both noise types, some extra statistical operations will allow to split the overall noise characterized into a contribution on row level, column level and pixel level. This gives very useful information on where to find the root cause of the noise issues. The overall measurement process will involve grabbing a particular number of dark images at various exposure times. Some simple statistical operations will split the noise into its various components.

At the end of the measurement cycle of noise in dark, the following parameters can be retrieved : offset of the sensor, noise floor in dark, conversion gain, dark current, dark signal-non-uniformity, total fixed-pattern noise, row level fixed-pattern noise, column-level fixed-pattern noise, pixel-level fixed pattern noise, temporal noise on row level, temporal noise on column level, temporal noise on pixel level, saturation level or full-well capacity.

Not only the measurement process will be explained, but also extensive comments will be given to the obtained results. In this way the course participants learns how to do the measurements, as well as how to do the interpretation of the results generated by means of the measurements in dark.