Non-uniformity in the response of spectral image elements is an inevitable phenomenon in hyperspectral imaging, which mainly manifests itself as the presence of band noise in the acquired hyperspectral data. This problem is prominent in the infrared band owing to the detector material, operating environment, and other factors. Non-uniformity is an important factor that can affect the quality of the hyperspectral data, which has a serious impact on both data analysis and applications and requires corrections via technical means wherever possible. This paper proposes a novel target-based non-uniformity self-correction method for infrared push-broom hyperspectral images. The Mars Mineralogical Spectrometer (MMS) onboard the Tianwen-1 orbiter was used as the research and application object. The model is constructed and applied to the target scene characteristics and detection patterns of Mars remote sensing exploration, which are combined with the causes of noise generation in the infrared spectral image bands. The design of the MMS dual-channel Visible-Near-Infrared (V-NIR) and Near-Mid-Infrared (N-MIR) co-field of view co-target detection and laboratory calibration data for the V-NIR spectral band can achieve non-uniformity corrections (NUCs). Therefore, for the MMS in-orbit Mars exploration mission, the method selected spectral data (920–1055 nm) characterized by a reduced atmospheric influence to iteratively obtain the homogeneous region, which was used to calculate the non-uniformity correction factor for the N-MIR spectral band. This method was compared, validated, and evaluated with other conventional methods using both laboratory and in-orbit hyperspectral data. The results showed that the experimental data corrections were comparable to laboratory calibrations, with a maximum relative deviation of <2.6%. These results prove that our method not only provides an excellent non-uniformity correction, but also ensures spectral fidelity. It can thus be used as a non-uniformity correction process for the MMS and similar hyperspectral imagers.
