A Multi-Spectral Temperature Field Reconstruction Technology under a Sparse Projection

In optical sparse projection reconstruction, the reconstruction of the tested field often requires the utilization of a priori knowledge to compensate for the lack of information due to the sparse projection angle. For situations where the radiation field of unknown materials is reconstructed or prior knowledge cannot be obtained, this paper proposes a multi-spectral temperature field reconstruction technology under a sparse projection. This technology utilizes the principles of multi-spectral temperature measurement technology, takes the correlation of radiation information between sub-regions of the temperature field as the optimization objective, and establishes statistical rules between the missing information by combining the equation constraint optimization algorithm and multi-spectral temperature measurement technology. Finally, the temperature field to be measured is reconstructed. The simulation and experimental tests show that, without any prior knowledge, the proposed method can reconstruct the temperature field under two projection angles, with an accuracy of 1.64 similar to 12.25%. Moreover, the projection angle is lower, and the robustness is stronger than that of the other methods.