Two-point linear and target and environment-based binary non-linear infrared detector heterogeneity correction method

Abstract

The invention discloses a two-point linear and target and environment-based binary non-linear infrared detector heterogeneity correction method. The two-point linear and target and environment-based binary non-linear infrared detector heterogeneity correction method comprises two-point linear heterogeneity correction and target and environment-based binary non-linear heterogeneity correction. The two-point linear heterogeneity correction comprises the following sub-steps of enabling a focal plane and a plane blackbody origin to be aligned through an optical system; calculating a response mean value of every detection element under high and low temperature and response mean values of all detection elements; calculating correction gain and offset of every detection element, and respectively storing inside a lookup table for utilization during correction; correcting the infrared image according to the gain and an offset coefficient in an LUT (Lookup Table). According to the two-point linear and target and environment-based binary non-linear infrared detector heterogeneity correction method, the response characteristics of a focal plane detector are completely described, different requirements on accuracy of resource expenditure, power consumption and application occasions are fully taken into consideration, the imaging quality of an infrared thermal infrared imager can be effectively improved, and the focal plane heterogeneity is reduced.

Description

technical field [0001] The invention relates to a method for correcting non-uniformity, in particular to a method for correcting non-uniformity of a binary nonlinear infrared detector based on two-point linearity and target and environment. Background technique [0002] Due to differences in the manufacturing process, there are differences in the spectral response characteristics of each detector element in an uncooled infrared focal plane array (Focal Plane Array, FPA) detector, which is called non-uniformity. The non-uniformity is manifested as Fixed Pattern Noise (FPN for short) superimposed on the scene in the output image of the detector. This noise seriously affects image quality and is not conducive to applications such as target detection and recognition. It needs to be suppressed or even eliminated through correction. Since non-uniformity drifts with time and environmental conditions, it is not sufficient to perform a blackbody-based calibration just prior to use. ...

AI Technical Summary

Problems solved by technology

This noise seriously affects image quality and is not conducive to applications such as target detection and recognition. It needs to be suppressed or even eliminated by correction.

As non-uniformity drifts with time and environmental conditions, a standard blackbody-based calibration is not sufficient just prior to use

However, periodic blackbody-based calibration during use not only needs to interrupt the working state, but also requires additional optical and mechanical equipment

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