Subpixel-Level-Accurate Algorithm for Removing Double-Layered Reflections from a Single Image

When photographers take pictures through glasses, image quality is sometimes degraded by window reflections. In this paper, we propose an algorithm to enhance the effectiveness of removing double-layered reflections from a single image. First, we apply subpixel-level autocorrelation to calculate the shift kernel of reflections. Secondly, a Gaussian-mixture-model (GMM) based layer separation technique is applied to estimate the initial transmission and reflection layers. In the refinement stage, we propose to add another GMM optimization flow to obtain the accurate transmission layer. Finally, a color and brightness adjustment step in Lab domain is used to provide better image quality. The qualitative and quantitative results show that the proposed method is very robust and effective.