Global Shutter

Global shutter (GS) imaging captures an entire scene simultaneously, unlike rolling shutter (RS) which scans row-by-row, leading to distortions in moving scenes. Current research focuses on computationally efficient methods to correct RS distortions and reconstruct high-frame-rate GS videos from RS footage, employing techniques like self-supervised learning, neural radiance fields, and adaptive warping algorithms. These advancements are significant because they improve the quality of video from widely used RS cameras, enabling more accurate computer vision applications and potentially reducing the cost and power consumption of high-speed imaging systems.