5.1 A Stacked Global-Shutter CMOS Imager with SC-Type Hybrid-GS Pixel and Self-Knee Point Calibration Single Frame HDR and On-Chip Binarization Algorithm for Smart Vision Applications

摘要

Request for smart vision related applications, such as face identification, VR/AR, gesture recognition, 3D imaging, and artificial intelligence (AI), has driven demand for high-performance global-shutter (GS) sensors. Most commercially available GS sensors use a charge-domain storage gate implementation, which suffers from serious light leakage and leads to lower shutter efficiency. This situation worsens when using a BSI fabrication process [1]. In addition, the traditional frame-based or line-based HDR method utilizing multiple exposures adds motion artifact to fast-moving objects, which defeats the purpose of having a global shutter. Moreover, some smart vision applications such as QR 2D barcode scanners and 3D facial recognition with structured light method need image sensors to “read” a certain pattern and “understand” the information within. However, image sensors usually capture a full image that needs to be further transferred to and processed by a companion SoC. Higher resolution and increased complexity of the target pattern pose a growing challenge to transfer and process the entire image at real time, also the required high power consumption lowers handheld device's battery life.