The advantage of this approach is that it reduces processing requirements, but the disadvantage is that it rejects many detector readouts instead of just one. The study proposes adding one byte per pixel to include flag bits showing saturation or cosmic ray impact, the number of samples used for signal intensity estimation, and the variance of the sample differences. The study assessed a number of options for cosmic ray removal and signal intensity estimation. Two variations of mean-based CRR were assessed, where one or two maximum deviants are rejected. The study identified two approaches to data compression, Rice compression and Wavelet compression, but only assessed the use of Wavelet compression.
Bright sources cause higher error, significantly affecting the overall performance of the approach.
The study also assessed the results if only 34 readouts are taken per exposure instead of 65. The study compared the processing requirements for 34 readouts per exposure and 65 readouts per exposure, and found that the processing requirements are reduced by a factor of 0.35 if only 34 readouts per exposure are taken. These results include compression, which accounted for less than 1 percent of the processing requirement. Later, they will propose use of a co-processor ASIC to perform cosmic ray rejection, reducing the number of DSP processors to 7 for the CRR processing cases. This requires about 18 GBytes of storage, but avoids significant uplink data rates.