The polarization angle optimization method based on image gray-scale feature analysis

To address the issue of suboptimal flare elimination using a fixed polarization angle in production workshops—due to complex workpiece placement, varying light source intensities, and incident light angles—this study proposes applying image grayscale histogram analysis. By comparing the changes in pixel counts corresponding to white flares across grayscale histograms at different polarization angles, the effectiveness of flare elimination is determined. This approach identifies the optimal polarization angle to reduce or eliminate white flare regions. First, a polarization model for surface reflection and a polarization-based glare elimination model are established to demonstrate the feasibility of using polarization principles for glare reduction. Then, combined with grayscale feature analysis, an optimization method for determining the polarization angle is derived. Experimental results demonstrate that the grayscale histogram effectively reflects brightness distribution changes in flare regions, showcasing the polarization filtering effect and providing reliable criteria for determining the optimal polarization angle. This method is easy to implement and suitable for optimizing image acquisition under complex lighting conditions.