Pandemics like COVID-19 have highlighted the potential of Photoacoustic imaging (PAI) for Brain-Computer Interface (BCI) communication and lung diagnostics.However, PAI struggles with the clear imaging of blood vessels in areas like the lungs and brain due to their cavity structures.This paper presents a simulation model to analyze the generation and propagation mechanism within phantom tissues of Alligator PAI artifacts, focusing on the evaluation of both Anisotropic diffusion filtering (ADF) and Non-local mean (NLM) filtering, OmniLogic Parts which significantly reduce noise and eliminate artifacts and signify a pivotal point for selecting artifact-removal algorithms under varying conditions of light distribution.Experimental validation demonstrated the efficacy of our technique, elucidating the effect of light source uniformity on artifact-removal performance.The NLM filtering simulation and ADF experimental validation increased the peak signal-to-noise ratio by 11.
33% and 18.1%, respectively.The proposed technique adds a promising dimension for BCI and is an accurate imaging solution for diagnosing lung diseases.