CAREER: Statistical modeling and real-time correction of nonuniformity in array sensors

该学院早期职业发展（CAREER）计划奖的研究部分是解决在卫星成像，空中监视和侦察，天文成像和目标识别中使用的红外和激光成像系统中图像退化的实时校正问题。 考虑的退化类型是由于阵列传感器和大气湍流的非理想特性。 阵列传感器性能的最大限制退化来自传感器响应的空间和时间非均匀性。 这项研究采用了一种统计实时校正方法，避免了需要昂贵的基于校准的校正技术，需要相机转向远离目标的校准期间。 基于模型的统计方法进行非均匀性校正是适应恢复图像退化的大气湍流。 在存在量子噪声的情况下，确定给定系统所需的最佳曝光时间（或帧数）的基本问题也正在解决。 在这项研究中开发的算法将通过研究者与政府和行业的合作努力在真实的系统中实现。 这项研究的教育组成部分包括旨在激励和激发本科工程专业学生和加强代顿地区研究生研究所（DAGSI）计划的结构，这是代顿地区高等教育系统的重要组成部分的活动。 这些教育活动包括：（1）通过改进某些现有的工程课程，向本科生和研究生展示实际研究成果;（2）通过交互式视频网络，向九所地方高等教育机构和DAGSI方案提供定期研讨会;（三）与本地业界及政府实验所合作，加强学生的实习训练;（4）在本科教育中积极吸收研究助理参与本研究。

The research component of this Faculty Early Career Development (CAREER) Program Award is addressing the problem of real-time correction of image degradation in infrared and laser imaging systems used in satellite imaging, aerial surveillance and reconnaissance, astronomical imaging, and target recognition. The types of degradation considered are due to the non-ideal characteristics of array sensors and atmospheric turbulence. The most limiting degradation in the performance of array sensors arises from the spatial and temporal nonuniformities in the sensors' responses. This research employs a statistical real-time-correction approach that avoids the need for costly calibration-based correction techniques that require the camera to steer away from the target for the duration of the calibration. The model-based statistical approach undertaken for nonuniformity correction is adapted to restore images degraded by atmospheric turbulence. The fundamental question of determining the optimal exposure time (or number of frames) needed for a given system in the presence of quantum noise is also being addressed. The algorithms developed in this research will be implemented in real systems through the investigator's collaborative efforts with the government and industry. The educational component of this research includes activities designed to motivate and excite undergraduate engineering students and strengthen the structure of the Dayton Area Graduate Studies Institute (DAGSI) Program that is a vital component of the Dayton-Area higher education system. These educational activities include: (1) demonstrating the practical research findings to undergraduate and graduate students by improving certain existing engineering courses; (2) offering periodical seminars available to nine local higher- education institutions and the DAGSI program through an interactive video network; (3) enhancing the practical training of students through collaboration with the local industry an d government laboratory; and, (4) actively involving the research assistants in this research in undergraduate education.