A Novel Reflection Removal Algorithm Using the Light Field Camera
Tingtian Li, Daniel Pak-Kong Lun · 2018
In daily photography, it is common that the captured images are superimposed with undesired reflection of another scene. Such reflection does not only reduce the visual quality of the target background scene, but also affects the subsequent processing on the image. Removing the reflection without any prior information of the background is a very challenging task. Traditional approaches often come with various assumptions, which are difficult to fulfil in general. In this paper, we propose a novel method to remove the reflection based on light field (LF) imaging. Via the epipolar plane image, we firstly devise a method to retrieve the depth map of the scene from an LF image. According to the depth value, the gradient points of the image are classified to belong to the background, reflection or shared layer. Finally, the background image is reconstructed from the estimated gradient points in the background and shared layers using a sparse optimization process. The proposed algorithm does not have the assumptions of the existing methods; thus, it is more robust. Experimental results show that the proposed algorithm outperforms the existing approaches both qualitatively and quantitatively.