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Method for quantifying image quality in push-broom hyperspectral cameras

机译:推扫式高光谱相机中图像质量的量化方法

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We propose a method for measuring and quantifying image quality in push-broom hyperspectral cameras in terms of spatial misregistration - such as keystone and variations in the point-spread-function across spectral channels - and image sharpness. The method is suitable for both traditional push-broom hyperspectral cameras where keystone is corrected in hardware and cameras where keystone is corrected in post-processing, such as resampling and mixel cameras. We show how the measured camera performance can be presented graphically in an intuitive and easy to understand way, comprising both image sharpness and spatial misregistration in the same figure. For the misregistration we suggest that both the mean standard deviation and the maximum value for each pixel are shown. We also suggest a possible additional parameter for quantifying camera performance: probability of misregistration being larger than a given threshold. Finally, we have quantified the performance of a HySpex SWIR 384 camera prototype using the suggested method. The method appears well suited for assessing camera quality and for comparing the performance of different hyperspectral imagers, and could become the future standard for how to measure and quantify the image quality of push-broom hyperspectral cameras.
机译:我们提出了一种用于测量和量化推扫式高光谱相机中图像质量的方法,包括空间重合失调(例如梯形失真和跨光谱通道的点扩展功能的变化)和图像清晰度。该方法既适用于在硬件中校正了梯形失真的传统推扫式高光谱摄像机,也适用于在后处理中校正了梯形失真的摄像机,例如重采样和混合摄像机。我们展示了如何以直观且易于理解的方式以图形方式呈现测得的相机性能,在同一张图中同时包括图像清晰度和空间重合失调。对于重合失调,我们建议同时显示每个像素的平均标准偏差和最大值。我们还建议了用于量化相机性能的其他可能参数:配准错误的概率大于给定阈值。最后,我们使用建议的方法量化了HySpex SWIR 384相机原型的性能。该方法似乎非常适合评估相机质量并比较不同的高光谱成像仪的性能,并且可能成为将来如何测量和量化推扫式高光谱相机的图像质量的标准。

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