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A 30-fps 192 脳 192 CMOS Image Sensor With Per-Frame Spatial-Temporal Coded Exposure for Compressive Focal-Stack Depth Sensing
IEEE Journal of Solid-State Circuits ( IF 4.6 ) Pub Date : 2022-03-01 , DOI: 10.1109/jssc.2022.3149916
Yi Luo 1 , Shahriar Mirabbasi 1
Affiliation  

In this article, we present a CMOS image sensor (CIS) for coded-exposure-based compressive focal-stack imaging. The proposed CIS has a pixel design, which includes two capacitive trans-impedance amplifiers (CTIAs) and a static random access memory (SRAM), and is capable of per-frame exposure encoding with adjustable spatiotemporal resolutions. A proof-of-concept CIS prototype with a 192 ×\times 192 pixel array is designed and fabricated in a 0.13- μm\mu \text{m} CMOS process with a pixel size of 12.6 ×\times 12.6 μm2\mu \text{m}^{2} . Operating at 30 frames per second (fps), the CIS demonstrates spatial–temporal coded exposure at a maximum rate of 768 masks/frame. The column-wise 10-bit single-slope (SS) analog-to-digital converter (ADC) includes a ramp-slope adaptation feature used for power optimization. During a frame of coded exposure, a linear focal sweep is implemented by a voice-coil motor (VCM) lens mounted in front of the proposed CIS. Through the sparse reconstruction of the coded image, a focal stack consisting of a volume of defocused images is used to synthesize the scene depth map. By introducing coded exposure, the proposed on-chip compressive focal-stack imaging approach facilitates a frame-saving method for passive depth sensing in machine vision and other imaging applications.

中文翻译:


具有每帧时空编码曝光的 30-fps 192 × 192 CMOS 图像传感器,用于压缩焦点堆栈深度传感



在本文中,我们提出了一种用于基于编码曝光的压缩焦点堆栈成像的 CMOS 图像传感器 (CIS)。所提出的 CIS 具有像素设计,其中包括两个电容跨阻放大器 (CTIA) 和一个静态随机存取存储器 (SRAM),并且能够以可调节时空分辨率进行每帧曝光编码。概念验证 CIS 原型具有 192 ×\times 192 像素阵列,采用 0.13- μm\mu \text{m} CMOS 工艺设计和制造,像素尺寸为 12.6 ×\times 12.6 μm2\mu \text {m}^{2} 。 CIS 以每秒 30 帧 (fps) 的速度运行,以最大 768 个掩模/帧的速率展示时空编码曝光。列式 10 位单斜率 (SS) 模数转换器 (ADC) 包括用于功率优化的斜坡-斜率自适应功能。在编码曝光帧期间,线性焦点扫描由安装在所提议的 CIS 前面的音圈电机 (VCM) 透镜实现。通过编码图像的稀疏重建,由大量散焦图像组成的焦点堆栈用于合成场景深度图。通过引入编码曝光,所提出的片上压缩焦点堆栈成像方法促进了机器视觉和其他成像应用中被动深度感测的帧节省方法。
更新日期:2022-03-01
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