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We propose a novel high dynamic range (HDR) video reconstruction method withnew tri-exposure quad-bayer sensors. Thanks to the larger number of exposuresets and their spatially uniform deployment over a frame, they are more robustto noise and spatial artifacts than previous spatially varying exposure (SVE)HDR video methods. Nonetheless, the motion blur from longer exposures, thenoise from short exposures, and inherent spatial artifacts of the SVE methodsremain huge obstacles. Additionally, temporal coherence must be taken intoaccount for the stability of video reconstruction. To tackle these challenges,we introduce a novel network architecture that divides-and-conquers theseproblems. In order to better adapt the network to the large dynamic range, wealso propose LDR-reconstruction loss that takes equal contributions from boththe highlighted and the shaded pixels of HDR frames. Through a series ofcomparisons and ablation studies, we show that the tri-exposure quad-bayer withour solution is more optimal to capture than previous reconstruction methods,particularly for the scenes with larger dynamic range and objects with motion.

HDR Video Reconstruction with Tri-Exposure Quad-Bayer Sensors