Separation of weak reflection from a single superimposed image using gradient profile sharpness
It is a massively ill-posed problem to separate a superimposed image into an object image of our interested object and an interference image of reflection. Previous studies relied on redundant information introduced by multiple exposure or multi-view configurations in the separation. Later some new methods proposed tailor-made constraints to remove reflection in specific conditions for a single superimposed image. However, the separated results of these methods always have a lot of residuals or a few tone distortions. In this paper, we aim to realize a clear separation of weak reflection for a single superimposed image. Since the reflection is weak and always out of focus, the resulted interference image would have a smoother edge map than the object image. We utilize this smoothness constraint to obtain an initial separation by classifying gradients according to GPS (gradient profile sharpness) computation. Then we propose a gradient validation framework to reduce the structural correlation between the object image and the interference image. This framework can well correct the misclassified gradients obtained in the initial separation. The experimental results demonstrate that our method can generate promising separation results with little residual or color distortions.