Field recovery from digital inline holographic images of composite propellant combustion base on denoising diffusion model

Abstract

Digital inline holography has gained extensive application in the optical diagnosis of solid propellant combustion. However, this method confronts several challenges. Firstly, the calculation time required for reconstruction and depth of field extension is excessively long. Secondly, the excessive smoke, airflow, and flame during combustion cause significant interference and poor reconstruction quality, which reduces the accuracy of particle identification. To address these issues, we have developed a holographic image reconstruction technique for aluminum particle combustion based on the Attention Mechanism, U-net, and Diffusion models. This approach enables end-to-end reconstruction of aluminum particle combustion holographic images, while effectively circumventing the interference of airflow combustion and flame.