SBIR Phase I: CLEAR-View - A Cost Effective Thermal Imaging Sensor

SBIR 第一阶段：CLEAR-View - 一款经济高效的热成像传感器

• 批准号: 0611278
• 负责人: Kamil Agi
• 金额: --
• 依托单位: K&A Wireless, LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-01 至 2007-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0611278&HistoricalAwards=false
• 关键词: SBIR; Phase; CLEAR; View; Cost

This Small Business Innovative Research (SBIR) Phase I project aims to design, test and implement a novel scene-based nonuniformity correction (SBNUC) algorithm for use in microbolometer-based uncooled thermal imagers. The approach relies on exploiting telescopic motion in the scene, in a video sequence, inherent in imagery acquired by a camera that is mounted in the front of an operating vehicle, to algebraically extract the nonuniformity-noise parameters in a dynamic fashion, without the need for the usual shutter-based calibration. The technology offers a real-time solution to nonuniformity correction for thermal imagers in automobiles while the camera is still imaging the scene, without any disruption of its operation. If successful, this approach would enable an alternate method to process changes and to reduce the cost of thermal and other imager technologies.The diversification of both amorphous-Si based and vanadium oxide (VOx) based microbolometer-detector technologies is currently limited by cost, FPN performance, and mechanical reliability (e.g. shutter). The proposed approach will provide the ability to apply the uncooled cost-effective microbolometer detector to markets where there is a need for a low-cost, shutter-free thermal imagers. The auto industry has already started employing microbolometer-based night-vision systems to improve safety during night driving. This project will also have a direct impact on a broad spectrum of sensing applications including lightweight vehicle or handheld night-vision systems, thermal imaging cameras used in forest-fire detection, and law-enforcement applications.

这个小型企业创新研究（SBIR）第一阶段项目旨在设计，测试和实施一种新的基于场景的非均匀性校正（SBNUC）算法，用于基于微测辐射热计的非制冷热成像仪。该方法依赖于利用伸缩运动的场景中，在视频序列中，固有的图像由安装在前面的操作车辆的摄像机，以代数提取的非均匀性噪声参数的动态方式，而不需要通常的基于快门的校准。该技术为汽车中的热成像仪提供了一种实时的非均匀性校正解决方案，同时相机仍在对场景进行成像，而不会中断其操作。 如果成功的话，这种方法将使一种替代的方法来处理变化，并降低热成像仪和其他成像仪技术的成本。基于非晶硅和氧化钒（VOx）的微测辐射热计-探测器技术的多样化目前受到成本、FPN性能和机械可靠性（例如快门）的限制。 所提出的方法将提供将非制冷的具有成本效益的微测辐射热计探测器应用于需要低成本、无快门的热成像仪的市场的能力。汽车行业已经开始使用基于微测辐射热计的夜视系统来提高夜间驾驶的安全性。该项目还将对广泛的传感应用产生直接影响，包括轻型车辆或手持夜视系统，用于森林火灾探测的热成像相机和执法应用。