<p dir="ltr">Polarization and spectral imaging technology has wide application prospects and economic value in environmental detection, target recognition, remote sensing detection and industrial detection. However, the acquisition of hyperspectral or spectro-polarimetric imaging data is difficult and expensive in general. This study aims to develop a synthetic thermal imaging dataset using computer simulation. The study seeks to explore the simulation performance of Monte-Carlo path tracing algorithm in the fields of spectroscopy and thermal imaging. The goal is to provide a novel tool for effective and accurate dataset generation for thermal imaging neural networks training.</p>