Ghost-free dual-exposure HDR for dynamic scenes

Fahd Bouzaraa, Ibrahim Halfaoui, Onay Urfalioglu

Abstract: High Dynamic Range Imaging (HDRI) and Exposure Fusion (EF) are methods of choice to computationally extend the dynamic range of images depicting real world scenes. Unfortunately, those methods are still prone to certain artifacts. Among others, the so-called Ghost Effect is the most critical HDR limitation when it comes to dealing with motion (camera or scene motion) in input Low Dynamic Range (LDR) images. This problem becomes more challenging when the input LDR image stack contains only a couple of images with large color differences, which is the case in the mobile phone domain. To address this issue, a de-ghosting step is required to preserve the quality of the final HDR images. In this paper, we propose a robust de-ghosting approach based on the detection and the elimination of the motion induced effects on the final HDR images. The proposed method performs efficiently in all cases even on scenarios where only two differently exposed images with large illumination variations are available as input. Compared to the state-of-the-art, our results exhibit significant visual improvement and artifact reduction. Furthermore, our approach has low computational cost and complexity, which enables an efficient implementation especially for mobile phone-related applications.