Abstract
Advances in infrared focal plane arrays allow thermal cameras to operate without active cooling equipment, however, the outputs of uncooled thermal cameras are closely related to their own temperatures, which degrades the temperature retrieval accuracy when ambient environment varies. In this paper, a novel radiometric calibration approach is proposed to decrease the errors derived from ambient temperature drift and internal heating. Firstly, a multivariate polynomial correction plus a second-order polynomial correction are implemented to stabilize the camera output derived from temporal non-uniformity. Afterwards, multi-point correction is applied to remove the fixed pattern noise caused by spatial non-uniformity. Finally, object temperature is calculated from thermal image gray values using the Planck-like approximation function. Experimental results demonstrated that the proposed method outperforms existing shutterless and shutter-based methods especially when uncooled thermal cameras are in unstable status.
Published Version
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