Visual salience and stack extension based ghost removal for high-dynamic-range imaging

High-dynamic-range imaging (HDRI) techniques are proposed to extend the dynamic range of captured images against sensor limitation. The key issue of multi-exposure fusion in HDRI is removing ghost artifacts caused by motion of moving objects and handheld cameras. This paper proposes a ghost-free HDRI algorithm based on visual salience and stack extension. To improve the accuracy of ghost areas detection, visual salience based bilateral motion detection is introduced to measure image differences. For exposure fusion, the proposed algorithm reduces brightness discontinuity and enhances details by stack extension, and rejects the information of ghost areas to avoid artifacts via fusion masks. Experiment results show that the proposed algorithm can remove ghost artifacts accurately for both static and handheld cameras, remain robust to scenes with complex motion and keep low complexity over recent advances including patch based method and rank minimization based method by 20.4% and 63.6% time savings on average.