Weighted sparse representation multi-scale transform fusion algorithm for high dynamic range imaging with a low-light dual-channel camera

Most imaging devices lose image information during the acquisition process due to their low dynamic range (LDR). Existing high dynamic range (HDR) imaging techniques have a trade-off with time or spatial resolution, resulting in potential motion blur or image misalignment. Current HDR methods are based on the fusion of multi-frame LDR images and can suffer from blurring of fine details, image aliasing, and image boundary effects. This study developed a dual-channel camera (DCC) to achieve HDR imaging, which can eliminate image motion blur and registration problems. Considering the output characteristics of the camera, we propose a weighted sparse representation multi-scale transform fusion algorithm, which fully preserves the original image information, while eliminating image aliasing and boundary problems in the fused image, resulting in high-quality HDR imaging.