The quality-control process of polarizer production is hampered by the presence of extremely-slight transparent aesthetic defects (ESTADs). The saturated imaging method based on stripe structured backlight can effectively improve the imaging contrast of ESTADs. However, the contrast is very sensitive to the saturation degree, which requires careful manual selection. This paper presents a saturation level-guided image enhancement method that is simple to deploy in industrial settings. First, a new definition of the saturation level for structured backlit imaging with translation, scale, and rotation invariance is proposed. Then, an empirical model of contrast versus saturation level is established. Using the contrast data measured at five saturation levels, the optimal saturation level can be estimated using the parameter optimization method. The experimental results demonstrate that the method is effective, easy to use, and an improvement of imaging effects for transparent thin-film defect detection algorithms.