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热红外高光谱成像仪光谱匹配盲元检测算法
引用本文:张长兴,刘成玉,亓洪兴,张东,蔡能斌.热红外高光谱成像仪光谱匹配盲元检测算法[J].红外与激光工程,2020,49(1):0104002-0104002(7).
作者姓名:张长兴  刘成玉  亓洪兴  张东  蔡能斌
作者单位:1. 中国科学院上海技术物理研究所 中国科学院空间主动光电技术重点实验室, 上海 200083;
摘    要:受红外焦平面阵列生产工艺及材料本身特性影响,红外焦平面阵列不可避免地存在盲元,严重困扰红外数据的处理与应用。光栅分光推扫式热红外高光谱成像仪一般以红外焦平面阵列的其中的一维作为光谱维进行推扫式成像,空间维只剩一维,与一般的热像仪具有二维空间维的成像机制有很大区别。常规的实验室定标法和开窗处理的场景检测方法不能满足该成像方式的盲元检测需求。以热红外高光谱成像仪中的盲元检测为目标,有针对性地提出了基于光谱匹配的盲元检测算法。该方法从光谱维角度出发,以不同温度实验室黑体定标数据生成温升光谱数据,在数据规则化处理的基础上,自动提取有效像元目标的伪光谱曲线,采用光谱角匹配的方式实现盲元的自动检测。以典型的热红外高光谱成像仪获取数据并开展盲元检测实验,结果表明该方法充分利用了热红外高光谱成像仪的光谱维信息,检测精度较高,盲元补偿后的数据可满足热红外高光谱数据的行业应用。

关 键 词:盲元检测    光谱匹配    热红外高光谱    红外焦平面阵列
收稿时间:2019-10-05

Blind pixel detection algorithm using spectral matching for thermal infared hyperspectral imager
Affiliation:1. Key Laboratory of Spatial Active Opto-eletronic Technique, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China;2. Shanghai Key Laboratory of Crime Scene Evidence, Shanghai 200083, China
Abstract:Due to the influence of infrared focal plane arrays production technology and material characteristics, blind pixels are inevitable in infrared focal plane arrays, which seriously affects the processing and application of infrared data. The push-broom thermal infrared hyperspectral imager which using grating system generally takes one dimension of the infrared focal plane arrays as the spectral dimension and the other dimension as the spatial dimension, which is quite different from the imaging mechanism of the thermal imager with two spatial dimensions. Conventional laboratory calibration and scene detection methods based on moving window cannot meet the requirements of blind pixel detection on the thermal infrared hyperspectral imager. A new blind pixel detection algorithm based on spectral angle matching was proposed to detect the blind pixels in thermal infrared hyperspectral imager. Taken spectral dimension information into account, this method generated temperature rise spectrum data from blackbody calibration data at different temperatures. Based on the basis of data regularization processing, the pseudo-spectral curve of effective pixels were extracted automatically, and the blind pixels were detected automatically by means of spectral angle matching. To validated the new blind pixel detection algorithm, a typical thermal infrared hyperspectral imager was used to collect image data and detecte the blind pixels of the imager. The results indicates that this method makes full use of spectral information of the thermal infrared hyperspectral imager and has high detection accuracy. The data after blind pixels compensation can satisfy the application of thermal infrared hyperspectral data.
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