# Master flat frame

A master flat frame is created from a set of raw flat frames. Unlike the dark frame, we normalize the source frames first to ensure equal mean value for all of them. This is correct, because the mean level of a flat frame depends on the intensity of the light source that was used to illuminate the camera. What we are seeking here is a ratio of sensitivity of a detector pixel to the mean sensitivity of all pixels. It would be natural to normalize the flat frames to a mean value of 1.0, but if we attempted to store such a normalized frame to a file storing each pixel value as an integer number, the quantization noise would destroy all our efforts. Therefore, we have to choose a value which is high enough the reduce the quantization noise. On the other hand, the allowed range of values that can be stored to a file is limited and depends on the number of bits reserved for each pixel. If we put the mean intensity too high, some of the pixels would be out of range. The value which the flat frames is normalized to is a configurable parameter, its default value of 10,000 provides a trade-off between quantization noise and the limited range, and it is appropriate in the vast majority of cases.

The steps are as follows: First, take each of the source frames, apply the robust mean algorithm (see chapter Robust mean) to compute its mean intensity, then normalize the frame by dividing each pixel value by the mean value and multiplying by the required mean value of 10,000. Next, apply the robust mean algorithm to normalized frames on pixel-by-pixel basis, while leaving out bad and overexposed pixels. If a pixel has an invalid value on all source frames, it is marked as a bad pixel on the resulting frame.