Gas detection based on infrared thermal imaging is applied in many areas, but it is generally applied as a qualitative detection method to observe the target area; on the other hand, quantitative research on gas concentration is less common, the measurement accuracy is poor, and the calculation method of concentration in the commonly adopted transmission model is also complicated. In this paper, based on the radiance transfer model of gas infrared imaging technology, the influence of gas concentration, gas temperature, and background temperature on gas imaging detection is investigated, a gas detection and concentration inversion method based on dual-temperature background points is proposed, and the effects of the choice of reference band on background temperature correction are analyzed in relation to the changing trend of dual-band radiance difference. To verify the effectiveness of this method, a gas detection system with dual-temperature background spots was constructed in this paper utilizing a cooled mid-wave infrared focal plane detector plus a reference filter and a measurement filter, which achieved a promising concentration accuracy of less than 10% for carbon dioxide at a detectable range. Meanwhile, an infrared imaging system with a noise equivalent temperature difference (NETD) of 40 mK was employed to simulate the detection of methane, which enables the detection and concentration inversion of methane gas at a minimum concentration of 500 ppm·m at a distance of 1 km, which proves the capability of long-range detection.

To overcome the limitations of traditional on-orbit modulation function transfer (MTF) measurement methods that are heavily dependent on natural features, scenery, artificial edges, and point source targets, this paper presents an on-orbit MTF measurement method of remote sensing imager based on the refined image kernel (RIK) acquired directly from remote sensing images. First, the kernel is estimated from some remote sensing sub-images with rich texture details by using an iterative support detection (ISD) algorithm; then, it is refined by central pixel energy concentration (EC) to obtain the RIK. Secondly, the MTF curves are calculated by interpolating RIK and Fourier transform. Finally, the final MTF is the average value of MTFs at Nyquist frequency acquired by each RIK. To demonstrate the feasibility and validity of this method, the MTFs were compared to the result of the ISO12233 edge method with an error of no more than 7%. The relative error of the measured results does not exceed 5% for image signal-to-noise ratio (SNR) above 20dB. The results obtained from the on-orbit MTF measurement using remote sensing images of the Jilin-1 satellite have a maximum error of less than 2% compared with the ISO12233 edge method. These demonstrate that the method proposed in this paper supplies highly accurate and robust results and can successfully increase the efficiency of on-orbit MTF measurement, providing a reference for high-frequency monitoring of satellite on-orbit stability and their optical imaging quality.