Studying the performance parameters on real infrared image/data and evaluation by application of the NUC algorithm

Studying the performance parameters on real infrared data and evaluation by application of the NUC algorithm is proposed in this paper. Non uniformities are mainly attributed to the difference in the photo-response of each detector in the FPA. Other degrading factors such as IRFPA temperature, finite lens aperture causing blur, finite photo responsivity of the detector; under sampling add to the non-uniformities. The spatial and temporal non-uniformities in infrared focal plane array (IRFPA) result a slowly varying pattern on the image thereby, degrading the resolving capabilities of thermal imaging system considerably. Studying the performance parameters on real infrared data and evaluation by application of the NUC algorithm is presented. The results are compared with the black body based calibration method. This approach results the same residual non uniformities as obtained using black body method. However, this approach offers the much required field upgradeability, making the system more robust giving same performance under all environmental conditions. Hardware architecture for implementing the algorithm in real time is given. The results show that residual non-uniformities 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.