This study proposes a method for damage probability distribution imaging of shear horizontal ( SH) waves in thin plate structures by introducing a denoising factor, aiming to improve the accuracy of damage detection in complex environments. Addressing factors such as thin plate deformation, environmental interference, system errors, and human operation in guided wave structural health monitoring, this method reduces the interference of noise signals by introducing a denoising factor. To mitigate the impact of these noise signals, this method introduces a denoising factor and employs an adaptive threshold based on local peak values to isolate damage, thereby significantly enhancing imaging effectiveness. The propagation characteristics of SH-waves in thin plate structures are analyzed, and experiments are conducted on steel plates for validation. Results demonstrate that compared to traditional RAPID imaging methods, this approach enables more accurate damage localization. Furthermore, the study explores the advantages of denoising factor-introduced tomography imaging in reducing noise influence and detecting multiple damages, providing theoretical and engineering support for SH wave based thin plate structure damage detection.