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• A data fusion approach with high spatiotemporal resolution for wall temperature measurement is reported. • This approach is tested at different number of thermocouples and the IR camera sampling rate. • This approach is validated against different experimental conditions. A high spatial and temporal resolution of wall temperature measurement is beneficial for liquid film cooling design for thermal protection of rocket engine combustor chamber. The conventional thermocouple method has a high sampling frequency up to 50 kHz, but it is based on point measurement. The infrared (IR) thermal technique can achieve a two-dimensional surface temperature measurement, but the current sampling frequency is limited to a few hundreds of Hz. Here we report the application of the data fusion approach, which is integrated with proper orthogonal decomposition (POD) and compressed sensing (CS) to reconstruct the temperature field of a wall with high spatiotemporal resolution. In this approach, the low-frequency IR thermal camera data was analyzed by POD to acquire the POD modes. The high-frequency thermocouple data with the POD modes were utilized to get the high-frequency mode coefficients by CS. Subsequently, the temperature information reconstruction was completed with POD modes and the mode coefficients. The data fusion method was applied to reconstruct the 250 × 400 pixels temperature field with a frequency of 100 Hz. Using 10 thermocouples and the IR camera with sampling frequency f = 2 Hz, the root mean square error (RMSE) of the reconstructed temperature field is 1.11%, which shows the reliability of the present approach. The less thermocouple and the lower IR camera sampling frequency leads to poorer reconstruction quality, though the effect of IR camera sampling frequency is less significant than the number of thermocouples. The optimized sensor number and sampling frequency were determined by the RMSE in this paper. The RMSE of the data fusion method with the initial temperature T 0 from 40 °C to 120 °C and the flow rate Q from 45 mL/min to 120 mL/min are less than 1.4%, which shows wide applicability of the present approach. A data fusion method which integrates the high spatial resolution IR camera data with the high temporal resolution thermocouple data for wall temperature measurement is reported. The typical steps are shown in above figure. The coherent structure is extracted from the IR camera data based on proper orthogonal decomposition (POD). The coefficients of POD modes are then optimized by the compressed sensing from thermocouple data. The average root mean square error (RMSE) of the reconstructed result with 105 points and 100 Hz is around 1.11%. This method is also validated against different wall temperature and jet flow rate conditions and largest RMSE is found to be less than 1.4%. [Display omitted] [ABSTRACT FROM AUTHOR]