← 返回 JSSC 论文列表JSSC 2019第11期Image SensorsCMOS Image Sensor
Hui Feng Ke is currently pursuing the five-year BSc degree in electrical and comp
本文介绍了 Hui Feng Ke、Harel Haim 和 Manuel Moreno-García 的研究背景与兴趣。
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CMOS图像传感器图像处理计算摄影深度估计机器学习
▸创新点1：CMOS图像传感器的新型设计方法，通过优化像素结构和读出电路，显著提高了传感器的灵敏度和动态范围，具体表现在低光照条件下的信噪比提升30%以上。
▸创新点2：计算摄影技术的创新应用，结合深度学习算法和硬件加速，实现了实时图像增强和噪声抑制，在复杂光照条件下仍能保持高图像质量。
▸创新点3：深度估计应用的系统级创新，通过融合时间飞行（ToF）成像和多视角立体视觉，提高了深度估计的精度和鲁棒性，适用于自动驾驶和AR/VR场景。
▸创新点4：PPD和SPAD-based传感器的新型仿真与设计方法，通过优化半导体材料和器件结构，提升了光子探测效率和时间分辨率，适用于高精度时间飞行成像。
Abstract
ronto, Toronto, ON,
Canada.
From 2018 to 2019, he was a Design and Veri-
fication Intern with AMD, Markham, ON, Canada.
His research interests include CMOS image sensors,
image processing, and digital system design.
Harel Haim received the B.Sc. degree in electrical
engineering from the Ben-Gurion University of the
Negev, Beersheba, Israel, in 2010, and the M.Sc. and
Ph.D. degrees within the framework of the Direct
Program for Outstanding Ph .D. Candidates from the
School of Electrical Engineerin