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Gas remote detection is useful for early warning of gas leakage and toxic chemicals. Optical gas imaging (OGI) built with an uncooled infrared camera is superior to cooled detectors in terms of cost. Current mainstream OGI technologies fall short in their detection of gases at ambient temperature and their ability to classify multiple gases. A multi-spectral uncooled imager is developed to try to solve these problems, which is constructed from a commercial uncooled thermal camera and wide band filters. To solve filter self-radiation and unevenness, a correction method is devised, with an ambient temperature blackbody placed in front and subtracted from the measured image. Based on waveband cutoffs, filters are classified into target-sensitive filters and background filters. Multi-spectra are simulated according to wide band filter transmittance, which can be used in gas classification. A sulfur hexafluoride (SF6) experiment is conducted outdoors at a distance of 10 m. An SVM model is trained to classify gas release in real time. Detection with a cold sky background is improved with the aid of data cube differences in a time sequence. The SF6 outdoor experiment concluded with preliminary effective results of ambient temperature gas remote detection.

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