A ghostfree contrast enhancement method for multiview images without depth information

High dynamic range (HDR) images greatly improve visual content quality, but pose challenges in processing, acquisition, and display. Images captured in real-world scenarios with multiple nonlinear cameras, extremely short unknown exposure time, and a shared light source present the additional challenges of incremental baseline and angle deviation amongst the cameras. The disparity maps in such conditions are not reliable; therefore, we propose a method that relies on the accurate detection and matching of feature points across adjacent viewpoints. We determine the exposure gain among the matched feature points in the involved views and design an image restoration method to restore multiview low dynamic range (MVLDR) images for each viewpoint. Finally, the fusion of these restored MVLDR images produces high-quality images for each viewpoint without capturing a series of bracketed exposure. Extensive experiments are conducted in controlled and uncontrolled conditions, and results prove that the proposed method competes for the state-of-the-arts. [Display omitted] •A ghost-free contrast enhancement method for low light images.•Multiview Lowlight input images with unknown geometry.•Accurate feature points detection and matching.•The contrast and dynamic range of the multiview lowlight images are improved.