Abstract In view of the current situation that the target optical remote sensing imaging simulation (ORSIS) is cumbersome and cannot be finely modeled, a method for obtaining the Spatially Varying Bidirectional Reflection Factor (SVBRF) of the target based on the hyper-spectral image sequence is proposed. Based on the characteristics of target surface illumination model, the bidirectional reflection factor (BRF) of target is extended to the SVBRF by using the characteristics of imaging spectrometer measure data which corresponding the image pixel with the spectrum. Using spatial projected geometric principle to calculate the spatial position of imaging spectrometer’s photographing point. The direction of pixel reflectance is determined by the direction vector between the pixel point in the image and the shooting position of the imaging spectrometer. Then the SVBRF of the target according to the pixel is obtained. Finally, field imaging experiments were carried out by imaging spectrometer to verify the establishment of the target SVBRF in this paper. By comparing with the traditional method, the BRF calculated processing efficiency is increased by 80%. The experimental results show that the method based on hyper-spectral image sequence can quickly obtain the SVBRF of a uniform target, and the target optical features are finely modeled to be in units of pixels and have good practicality.

中文翻译：

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一种基于高光谱图像序列的目标空间变化双向反射系数计算方法

摘要 针对当前目标光学遥感成像仿真（ORSIS）繁琐且无法精细建模的现状，提出一种基于高光谱图像序列的目标空间变化双向反射系数（SVBRF）方法。被提议。基于目标表面照明模型的特点，利用成像光谱仪测量数据与光谱图像像素对应的特性，将目标的双向反射系数(BRF)扩展为SVBRF。利用空间投影几何原理计算成像光谱仪拍摄点的空间位置。像素反射的方向由图像中像素点与成像光谱仪拍摄位置之间的方向向量决定。然后根据像素得到目标的SVBRF。最后，通过成像光谱仪进行了场成像实验，验证了本文目标SVBRF的建立。与传统方法相比，BRF计算的处理效率提高了80%。实验结果表明，基于高光谱图像序列的方法可以快速获得均匀目标的SVBRF，并且目标光学特征被精细建模为以像素为单位，具有很好的实用性。通过成像光谱仪进行场成像实验，验证了本文目标SVBRF的建立。与传统方法相比，BRF计算的处理效率提高了80%。实验结果表明，基于高光谱图像序列的方法可以快速获得均匀目标的SVBRF，并且目标光学特征被精细建模为以像素为单位，具有良好的实用性。通过成像光谱仪进行场成像实验，验证了本文目标SVBRF的建立。与传统方法相比，BRF计算的处理效率提高了80%。实验结果表明，基于高光谱图像序列的方法可以快速获得均匀目标的SVBRF，并且目标光学特征被精细建模为以像素为单位，具有很好的实用性。