红外, 2017, 38 (4): 44, 网络出版: 2017-06-09  

一种基于卡尔曼的红外相机动态范围自适应调整算法

An Adaptive Adjustment Algorithm for Dynamic Range of Infrared Camera Based on Kalman
作者单位
1 中国科学院上海技术物理研究所, 上海 200083
2 中国科学院大学, 北京 100049
摘要
卡尔曼算法在目标跟踪、风向预测、非均匀性矫正领域都有着广泛应用。提出了用卡尔曼算法进行线列相机扫描灰度值的预测。根据线列探测器的实时扫描, 得出了灰度直方图的变化, 并将这一过程归一化到卡尔曼公式中; 用递推法快速测出了下一时间灰度的统计分布, 间接预测了积分时间, 最终达到了红外线列探测器动态范围自适应控制的目的。采用多幅8 bit图像为不同场景提供仿真环境, 最终快速稳定地预测出了下一阶段的灰度分布统计图。结果为红外线列相机扫描提供了智能化解决方案。
Abstract
Kalman algorithm is widely used in the fields of target tracking, wind direction prediction and nonuniformity correction. The prediction of scanning gray value of a linear array camera by Kalman algorithm is proposed. According to thereal-time scanning of the linear array detector, the change in the gray level histogram is derived and normalized into Kalman’s formula. The statistical distribution of next time gray level is measured quickly by a recursive method. The integration time is predicted indirectly. Finally, the adaptive control of the dynamic range of the linear infrared detector is achieved. Several 8 bit images are used to provide simulation environment for different scenes. Then, the gray level distribution statistics in neat stage is predicted quickly and stably. The result provides an intelligent solution for the scanning of the linear array infrared camera.

沈苏文, 林长青. 一种基于卡尔曼的红外相机动态范围自适应调整算法[J]. 红外, 2017, 38(4): 44. SHEN Su-wen, LIN Chang-qing. An Adaptive Adjustment Algorithm for Dynamic Range of Infrared Camera Based on Kalman[J]. INFRARED, 2017, 38(4): 44.

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!