CMOS image sensor design with programmable spatial-temporal exposure for machine vision and computational imaging applications
department or school: Applied Science, Faculty of
department or school: Electrical and Computer Engineering, Department of
data provider: DSpace
degree campus: UBCV
creator: Luo, Yi
issued: 2021-10-31T07:00:00Z
issued: 2020
related degree: Doctor of Philosophy - PhD
degree grantor: University of British Columbia
description: Compressive sensing, as one of computational imaging techniques, employs exposure encoding of cameras. Currently, as coded exposure is not supported monolithically on image sensors, computational cameras rely on discrete optical modulators to implement compressive sensing. In this thesis, we propose image sensor designs that are capable of per-frame spatial-temporal exposure encoding. We propose merging exposure-programmable pixels, which consist of charge modulators and exposure-code memory, into the imager design. Through pixel-wise exposure manipulation in every frame of image capture, compressive sensing and its related imaging applications are extended to the sensor node with significant benefits of high optical throughput, improved power efficiency, and compact footprint. In the design of exposure-programmable pixels, four types of pixel architectures are proposed. The capacitive-transimpedance-amplifier-based pixels are advantageous in sensitivity and charge-transfer speed, while the other two which use active-pixel-sensor-based structures offer a more compact size and circuit simplicity. To exploit the full potential of proposed pixel designs, the image sensor architecture is correspondingly modified as compared to the conventional image sensor designs. To evaluate the feasibility and performance of the proposed designs, two prototype image sensors are fabricated in a CMOS process. From experimental results, both conventional non-intermittent exposure and per-frame spatial-temporal coded exposure are verified. In demonstration of on-chip compressive sensing applications, two examples from high-speed imaging and compressive focal-stack depth sensing are presented. By performing compressive sensing at the sensor level, the CMOS image sensor designs introduced in this work further pave the way to on-chip computational imaging and facilitate implementation of many emerging applications in the machine vision paradigm.
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/76375
note: CMOS IMAGE SENSOR DESIGN WITH PROGRAMMABLE SPATIAL-TEMPORAL EXPOSURE FOR MACHINE VISION AND COMPUTATIONAL IMAGING APPLICATIONS by YI LUO B.A.Sc, University of Regina, 2012 M.A.Sc., The University of British Columbia, 2015 A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Electrical and Computer Engineering) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) October 2020 © Yi Luo, 2020 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: CMOS Image Sensor Design with Programmable Spatial-Temporal Exposure for Machine Vision and Computational Imaging Applications submitted by Yi Luo in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Electrical and Computer Engineering Examining Committee: Prof. Shahriar Mirabbasi, Electrical and Computer Engineering Supervisor Prof. Robert Rohling, Electrical and Computer Engineering Supervisory Committee Member Prof. Mieszko Lis, Electrical and Computer Engineering Supervisory Committee Member Prof. Jim Little, Computer Science University Examiner Prof. Panos Nasiopoulos, Electrical and Computer Engineering University Examiner iii Abstract Compressive sensing, as one of computational imaging techniques, employs exposure encoding of cameras. Currently, as coded exposure is not supported monolithically on image sensors, computational cameras rely on discrete optical modulators to implement compressive sensing. In this thesis, we propose image sensor designs that are capable of per-frame spatial-temporal exposure encoding. We propose merging exposure-programmable pixels, which consist of charge modulators and exposure-code memory, into the imager design. Through pixel-wise exposure manipulation in every frame of image capture, compressive sensing and its related imaging applications are …
has type: Thesis/Dissertation
date issued: 2020-11
is shown at: 10.14288/1.0394822
language: eng
degree discipline: Electrical and Computer Engineering
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
type: Text
identifier URI: http://hdl.handle.net/2429/76375