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Per-Pixel Coded-Exposure CMOS Image Sensors by Navid

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Per-Pixel Coded-Exposure CMOS Image Sensors by Navid Per-Pixel Coded-Exposure CMOS Image Sensors by Navid Sarhangnejad A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Department of The Edward S. Rogers Sr. Department of Electrical and Computer Engineering. University of Toronto © Copyright by Navid Sarhangnejad 2021 Abstract Per-Pixel Coded-Exposure CMOS Image Sensors Navid Sarhangnejad Doctor of Philosophy Department of The Edward S. Rogers Sr. Department of Electrical and Computer Engineering. University of Toronto 2021 The ever-growing demand for applications of cameras necessitate research not only on improving the performance of image sensors but also on new image sensor architectures. One of the most recent image sensor architectures, based on coded-exposure pixels (CEP), allows for the programmability of exposure time at the pixel level, and allows for imaging in new ways that were not possible so far. In this thesis, first a comparison of different photo-detectors is presented to highlight their operation principle as well as their capabilities. Five photo-detector architectures are simulated to compare the most important specifications in CEP cameras, namely sensitivity and tap-contrast. Next, a first prototype, a CEP image sensor based on photogate (PG) pixels, is presented. The sensor has a total resolution of 180 × 160 pixels and is fabricated in 0:35µm CMOS technology. Dual-tap pixels with per-tap conversion gain are proposed, where the photogenerated charges in the pixel are collected in one of the taps based on the code stored in the pixel at each interval of the exposure. The second prototype is an image sensor based on pinned-photodiode (PPD) pixels. The sensor is fabricated in a 0:11µm CMOS technology with the main array consisting of 244 × 162 pixels. The dual-tap pixel proposed in this work has the same conversion gain for the two taps but provides per-tap adjustable gain in the readout. The array ii operates at a maximum subframe rate of 180Hz, which is equivalent to 4 subframes per frame at 25fps considering the overhead time of frame readout. The sensor is deployed in two different single-shot 3D computational imaging techniques. Finally, an architecture based on global-shutter PPD pixels is presented allowing the implementation of smallest CEP pixels (7µm pitch) reported to date. The sensor is fabricated in 0:11µm CMOS technology with a resolution of 312 × 320 pixels. In the proposed pixel, a pinned storage diode operates as a charge memory to pipeline the charge generation and charge sorting operations. At a subframe rate of 2:7kHz, a reasonable tap- contrast of more than 90% is measured. Finally, a few different computational imaging techniques that are demonstrated with this camera are presented. iii Acknowledgements I want to extend my gratitude to professor Roman Genov, my direct Ph.D. supervisor, for giving me the opportunity to be part of his team, for his continuous support and his insight. During the time at Roman's group, he provided the tools and resources needed for my research. Recruiting post-docs and new grad students to help on different aspects of the project was a significant help in completing my program. Because of his approach, I learned a lot more than I initially expected from a Ph.D program by the opportunity to work with several grad students and conduct many undergrad students on different aspects of the project. I would also like to express my gratitude to professor Kiriakos N. Kutulakos, my Ph.D. co-supervisor, for his priceless support, vision and contributions. The basis of my research stem from his group's extraordinary work on computational imaging. I consider myself very lucky to have Kyros as a co-advisor. His patience to listen to my ideas, detailed explanations and brainstorming sessions were crucial in completing my research. I would like to thank my defense committee members, professor Ali Sheikholeslami and professor Antonio Liscidini for reviewing my thesis and providing constructive com- ments. Also, I would Like to thank external examiner Prof. Franco Zappa for taking part in my defense and providing his valuable feedback. I also would like to thank Dr. David Stoppa and his team for giving me the opportu- nity to join them at FBK IRIS for two months. It was a significant learning opportunity for me, especially with the support of Manuel Moreno Garcia. My Ph.D. started with working with Matthew P. O'Toole and Hyunjoong Lee on a computational imaging project, and my research became part of this project. They were outstanding colleagues and I learned a lot from them. I want to thank them for their priceless help and patience to educate me. I would like to thank other team mates, and simultaneously great friends, that contributed to the project and had paramount contributions to what we achieved together. They are Nikola Katic (a.k.a Johnny, the iv calm and wise guy that I could talk to regarding any topic and he would never let me down), Mian Wei (Mr. finisher, gets the demo done in a matter of days while educating us on how the demo actually works), Gairik Dutta (The energetic guy, analog designer working 24/7 in black leather jacket!), Nikita Gusev (The laser specialist, energetic and fun but unfortunately not that good at foosball!), Rahul Gulve (The mastermind, knows and works on everything and gets the issues fixed), Zhengfan Xia (The magician, We never understood when or how, but he was getting the Python/C++ codes done in very short time), and Harel Haim (The guide, answering my never ending silly computational imaging questions). They are all great friends, and I learned a lot from them through several tape-outs, prototyping, measurement and demonstrations. Out of many people from BA5158, only Javid Musayev had the title of "my best friend". Although he tries to duplicate my name, but I am not mad at him. He is a great friend in any possible way that one can ask for. I want to thank him for being such an incredible mate. I would like to thank Hossein Kassiri Bidhendi, Nima Soltani and Arshya Feyzi for the first months and year that I joined the team. They were great friends who helped me in settling in the city, as well as in the group. They provided a lot of help on the possibilities of working with undergrad students, writing proposals and lab management. I would also like to acknowledge my U of T colleagues, who made the Ph.D. expe- rience a much more pleasant and memorable one for me. I would like to thank Enver Kilinc, Gerald O'Leary, Maged ElAnsary, Wilfred Cho, Mohammad Reza Pazhouhan- deh, Camilo Tejeiro, Jose Sales Filho, Farhad Ramezankhani, Farrokh Etezadi, Saeed Reza Khosravirad, Navid Samavati, Foad Arvani, Amer Samarah, Chuanwei (Jason) Li, Keiming Kwong, Amirali Amirsoleimani, Jianxiong (Jay) Xu, Asish Abraham, Sadegh Dadash, Masumi Shibata, Ahmed Elian, Mahdi Marsousi, Samira Karimelahi, Hamed Sadeghi, Sevil Zeynep Lulec, Robert Baker, Daniel Rozhko, Mario Milicevic, Andrew Shorten, and Jin Hee Kim. I am also grateful to ECE staff members Jennifer Rodriguez, v Jaro Pristupa, Darlene Gorzo, and Jayne Leake and who helped me in different ways. It was a fortunate opportunity to mentor many bright graduate and undergraduate students who also contributed to my research. Hence I would like to thank Kevin Lee, Hardik Patel, Chengzhi (Winston) Liu, Peter Li, Terrence Cole Millar, Nafis Ahbab, Hsin-Yu Lo, Anas Ahmed Jamil, Shakthi Sanjana Seerala, Hui Feng (Jackie) Ke, Hui Di (Wendy) Wang, Jinzhuo (Sarah) Tang, Gilead Posluns, and Shichen Lu. I also want to thank the team at Huawei Technologies Canada, for accepting me in their team long time before I graduate from my Ph.D. program. I would like to thank Be- hzad Dehlaghi Jadid, Alireza Sharif-Bakhtiar, Mohammad Sadegh Jalali, Shayan Shahramian, Joshua Liang, Hossein Shakiba, Jingxuan Chen, Summer Zhu, Yingying Fu, Dustin Dun- well, and David Cassan as well as all the other colleagues. I want to thank my parents, brother and sisters for always supporting me and believing in me in my choices. I'd like to also thank my in-laws for their kindness and support. I am grateful for my beautiful little daughter, Ava, that made life colourful and was patient for me to finish my Ph.D. program. And finally, I am beyond grateful for all the support and kindness that my wife had for me during this time. Sheida made it possible for me to go through all the stress and hardships, and I want to dedicate this thesis to her and Ava. vi Contents Acknowledgements iv Contents vii List of Figures x List of Tables xvi 1 Introduction 1 1.1 CMOS image sensor background . .2 1.1.1 Imaging system pipeline . .2 1.1.2 Image sensor architectures . .4 1.1.3 Pixel operation . .5 1.1.4 Photosensing principle . .6 1.1.5 Performance metrics . .9 1.2 Thesis motivation: coded-exposure imagers . 13 1.3 Thesis objectives . 19 1.4 Thesis outline . 20 2 Comparison of photodetectors for coded-exposure pixels 22 2.1 Introduction . 23 2.2 Photodetector architectures . 25 vii 2.2.1 Operational speed . 25 2.2.2 Architecture choices . 27 2.2.3 Dual-tap architectures . 28 2.3 Comparison of dual-tap pixels . 31 2.3.1 Cross-section of the pixels . 31 2.3.2 Simulated electrostatic potential diagrams . 34 2.3.3 Simulated sensitivity and contrast . 36 2.3.4 Comparisons in literature . 40 2.4 Considerations for in-pixel circuitry . 43 2.4.1 Capacitors . 43 2.4.2 Storage diodes . 43 2.4.3 In-pixel transistors .
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