NUC Algorithm for Correcting Gain and Offset Non-uniformities

This paper describes a model for gain and offset non-uniformities and correction algorithm for nonuniformities. The infrared sensor model determines the number of photoelectrons generated from total incident flux and relates these electrons with integration time. It includes gain and offset non-uniformities in infrared sensor. A methodology for calibrating the sensor non-uniformities is presented. The uncorrected infrared data is collected by exposing the infrared sensor against a very high emissive source such as black body or sky. This data is then used for sensor calibration. This algorithm is tested on cooled infrared imaging system. The results show that residual nonuniformities are reduced from 6% to less that 0.6% after performing the correction. Further, it is observed that the system is fully calibrated at two calibration points. The spatial noise after non-uniformity correction is compared with the temporal noise of the system and the results illustrates that the spatial noise is reduced significantly lower than the temporal noise of the system. This approach offers the upgradeability of gain and offset coefficients, thus making the system more robust by giving same performance under all environmental conditions.