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

SBIR 第二阶段：CLEAR-View - 一款经济高效的热成像传感器

• 批准号: 0724500
• 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: 2007
• 资助国家: 美国
• 起止时间: 2007-09-15 至 2010-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0724500&HistoricalAwards=false
• 关键词: SBIR; Phase; II; CLEAR; View

This NSF SBIR Phase II project aims to develop and produce a novel suite of algorithms to enhance the performance of thermal imagers, offering real-time solutions in the automotive, surveillance and other segments of the thermal imaging market. The proposed algorithm is integrated with noise-infested, uncooled microbolometer infrared cameras, elevating their performance and offering manufacturing-cost reductions while adding new features and capabilities. At the heart of the approach is a Scene-Based NonUniformity Correction (SBNUC) algorithm, which works to correct the fixed-pattern noise resulting from nonuniform detector-to-detector responses in the focal-pane array. The novel SBNUC approach relies on exploiting the presence of minute amounts of scene/camera motion in a video sequence, naturally present in almost all applications, to algebraically extract the nonuniformity-noise parameters in a dynamic fashion, without the need for a mechanical shutter, as done conventionally. This approach improves the camera's reliability. If successfully commercialized, the largest market is in the automotive sector, where the lower cost and improved performance of the device can potentially lead to tens of millions of dollars from new installs of collision-avoidance systems in cars and trucks. The enhanced features and lower costs offered by this technology also offer the potential of expanding the use of thermal imaging in other applications. In the firefighting market segment, equipping every firefighter with a thermal imager will reduce the number of fatalities due to smoke inhalation, heat, and response efficiency. In security applications, more information will be delivered at a higher level of quality.

NSF SBIR二期项目旨在开发和生产一套新的算法，以提高热像仪的性能，为汽车、监控和其他热成像市场提供实时解决方案。该算法与无噪声、非冷却的微热红外摄像机相结合，提高了红外摄像机的性能，降低了制造成本，同时增加了新的特性和功能。该方法的核心是基于场景的非均匀性校正（SBNUC）算法，该算法用于校正焦面板阵列中由探测器对探测器响应不均匀引起的固定模式噪声。这种新颖的snuc方法依赖于利用视频序列中自然存在的少量场景/摄像机运动，以动态方式代数提取非均匀性噪声参数，而不需要像传统方法那样使用机械快门。这种方法提高了摄像机的可靠性。如果成功实现商业化，最大的市场将是汽车行业，该设备的低成本和更高的性能可能会为汽车和卡车的新防撞系统安装带来数千万美元的收入。该技术所提供的增强功能和更低的成本也为热成像在其他应用中的扩展提供了潜力。在消防细分市场，为每位消防员配备热成像仪将减少因吸入烟雾、热量和反应效率而导致的死亡人数。在安全应用程序中，更多的信息将以更高的质量水平交付。