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
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
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5.1 用于智能视觉应用的具有 SC 型混合 GS 像素和自拐点校准单帧 HDR 和片上二值化算法的堆叠全局快门 CMOS 成像器
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
C. Yiu
中科院分区：
文献类型：
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作者：
Chen Xu;Y. Mo;Guanjing Ren;Weijian Ma;Xin Wang;Wenjie Shi;Ji;Ke Shao;Haojie Wang;P. Xiao;Zexu Shao;Xiao Xie;Xiaoyong Wang;C. Yiu
人脸识别、VR/AR、手势识别、3D成像和人工智能(AI)等智能视觉相关应用的需求推动了对高性能全局快门(GS)传感器的需求。大多数商用GS传感器使用电荷域存储栅极实现，这存在严重的漏光问题，并导致快门效率较低。当使用BSI制造工艺时，这种情况变得更糟[1]。此外，传统的基于帧或基于线的HDR方法利用多次曝光增加了运动伪影到快速移动的对象，这与拥有全局快门的目的背道而驰。此外，一些智能视觉应用程序，如QR 2D条形码扫描仪和结构光3D人脸识别方法，需要图像传感器来“读取”某个图案，并“理解”其中的信息。然而，图像传感器通常捕获需要进一步传输到配套SoC并由其处理的完整图像。更高的分辨率和更高的目标图案复杂度对整个图像的实时传输和处理提出了越来越大的挑战，同时所需的高功耗降低了手持设备的电池寿命。
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.