High-temperature processes can have a direct impact on the state and physicochemical properties of materials, making high-temperature measurements important in scientific research, materials processing, and equipment evaluation. A temperature measurement method of color CCD based on matrix search is reported in this paper. In this method, the traditional temperature reverse calculation process is transformed into the forward matrix search process, and the process parameters such as medium absorption gamma correction are incorporated, which saves the calculation resources and is closer to the actual temperature measurement conditions. A temperature measurement process and a temperature visualization procedure are designed for this high-temperature measurement method, the flame temperature measurement experiments are carried out, and the error results are obtained. By comparing the solution results and chrominance deviation distance between the perturbation emissivity model and the non-perturbation emissivity model, the robustness of the solution method is discussed.

Nowadays, the infrared imaging technology is widely used in space detection, land inspection, security monitoring and other fields. In order to ensure the accuracy of the infrared target recognition, it is necessary to completely understand the radiation characteristics of the target. The target radiation characteristics need to be measured in out-field condition, and the large area blackbody radiation source need to be used for field radiation parameters calibration to the measuring equipment of target characteristics. A large area blackbody radiation source was designed. The radiator was made of aluminum material with black treatment, and the proportion integral differential (PID) control algorithm was adopted by the temperature control of large area blackbody radiation source. When the actual ambient temperature was 26.8 ℃ and the humidity was 60%, the radiation parameters of the target characteristics measuring equipment were calibrated. The test data show that the uncertainty of the radiation temperature measurement is 0.4 ℃ ( k = 2), and good application effect is achieved.

Unmanned aerial vehicles (UAVs) are increasingly utilized across military, civilian, and agricultural sectors, necessitating accurate and efficient 3D target localization. Traditional 2D detectors lack depth perception, while stereo vision and LiDAR have range-dependent and hardware limitations, respectively. To address these limitations, we propose a monocular 3D localization framework using a prebuilt, georegistered triangular mesh. A two-dimensional grid indexes the mesh, and a progressive multi-scale strategy loads high-resolution blocks for ray–mesh intersection. The nearest intersection is used only for targets supported by, or projectable onto, the mapped surface. Unity experiments give localization RMSEs of 0.0193–0.9229 m; a real UAV field log gives a pooled static-track repeatability RMSE of 0.0849 m. Repeated timing measurements give mean per-query times of 5.08 ms and 1.03 ms for full-resolution and progressive search, respectively.