This paper addresses the problem of inaccurate emissivity presets for multispectral temperature measurements of aero-engine turbine blades and proposes a narrow-band spectral window moving temperature inversion algorithm that does not rely on an assumed emissivity model. As the emissivity of the measured object changes slowly over the narrow spectral window, the temperature corresponding to the normalized spectral radiation intensity for each window in the set temperature range is calculated using the Mahalanobis distance coefficient. The temperature error is less than 1.33% relative to thermocouple measurements when using this algorithm to perform temperature inversion on the experimental spectrum curves for different types of alloy samples. Furthermore, a two-dimensional spectral temperature field measurement platform was built, and the surface temperature fields of alloy samples were reconstructed using the narrow-band spectral window moving algorithm. The proposed algorithm is shown to provide high-precision inversion of the temperature field without presetting the emissivity model, which gives a new processing concept for the application of infrared spectral temperature measurements.

Infrared imaging spectrometers detect and identify targets by collecting spectral and image information. However, when detecting small temperature differences and dynamic targets, the accuracy of infrared detection is reduced, the traditional scanning structure detection time is longer, the real-time performance is poor and it is easy to introduce motion artifacts. This paper proposes an infrared polarization snapshot spectral imaging system (PSIFTIS) based on a polarizer array, a lens array and a roof-shaped stepped micromirror. Polarized light can solve the problem of small-temperature-difference target recognition by characterizing the surface properties of materials. Lens arrays utilize multi-aperture imaging to achieve snapshot detection of targets. The system can obtain 4D data information, including polarization, in a single measurement cycle. This study completed the overall optical design of a PSIFTIS and an optical simulation experiment using it. Finally, a system prototype was built in the laboratory and a polarization spectrum detection experiment was carried out. The experimental results show that the PSIFTIS could accurately obtain the polarization spectrum information for the target, the spectral resolution reached 7.8 cm−1 and the Stokes measurement error was less than 5%.

Edge detection is the basis of image analysis and image processing. The wavelet modulus maxima algorithm is a widely used edge-detection algorithm. The algorithm has the advantages of strong anti-noise ability and high precision of edge location, but it still cannot accurately obtain edge information for low-contrast images. Therefore, this paper proposes an improved wavelet mode maximum edge algorithm for the fusion of light intensity and degree of polarization. The improved wavelet mode maximum algorithm was used to extract the edges of a light intensity image and degree of polarization image, and then refine and fuse the two edges to obtain the final edge information. Simulation experiments showed that the edge image obtained by the edge-detection algorithm in this paper had a clearer outline and better connectivity.