星载遥感短波红外高速高光谱成像仪坏像元识别

Identification of bad pixels in shortwave infrared high-speed hyperspectral imager for spaceborne remote sensing

为改善干涉成像短波红外高速高光谱成像仪的坏像元对复原光谱的影响,利用高光谱成像仪测试流程建立了坏像元识别模板,以提高坏像元识别效率。首先,按照高光谱成像仪测试流程设置增益模板和帧频模板并采集图像数据,依据正常像元增益响应设定合理判定阈值Th1,识别不同增益下异常像元并记录对应坐标值;再依据正常像元帧频响应灰度值设定合理判定阈值Th2,识别不同帧频下异常像元并记录坐标值。最后,对比增益模板和帧频模板判定的异常像元,融合确定坏像元。实验结果表明基于增益模板和帧频模板的识别方法在不增加设备研制测试成本的同时有效识别出短波红外高光谱成像仪探测器的坏像元,为可靠识别短波红外高光谱成像仪坏像元提供了一种低成本、高效可靠的新方法,提高了干涉成像高光谱成像仪光谱反演准确性。

To reduce the influence of bad pixels in large-aperture interferometric imaging shortwave infrared high-speed hyperspectral imagers on recovering spectra, a bad pixel identification template was established using a hyperspectral imager test process to effectively raise the efficiency of identification of bad pixels. First, image data were collected based on the gain template and frame-rate template for the hyperspectral imager test. Then,the judgment threshold Th1was set reasonably according to the gain response of normal pixels to identify abnormal pixels under different gains and record the corresponding coordinate values, and the judgment threshold Th2was set reasonably according to the frame-rate response gray values of normal pixels to identify abnormal pixels under different frame rates and record the coordinate values. Finally, after the abnormal pixels identified by the gain template and those identified by the frame-rate template were compared, they were used together to identify bad pixels. The experimental results show that the identification method based on the gain and frame-rate templates can effectively identify bad pixels in a shortwave infrared hyperspectral imager detector without increasing the cost of equipment development and testing, while providing an economical, practical, efficient, and reliable technical means for correcting bad pixels in a shortwave infrared hyperspectral imager. The method also offers a useful reference to improve the accuracy of inversion of interferometric imaging hyperspectral imager spectral data.