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Reconstruction of multispectral images from spectrally coded light fields of flat scenes

机译:从平面场景的光谱编码光场重建多光谱图像

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摘要

We present a novel method to reconstruct multispectral images of flat objects from spectrally coded light fields as taken by an unfocused light field camera with a spectrally coded microlens array. In this sense, the spectrally coded light field camera is used as a multispectral snapshot imager, acquiring a multispectral datacube in a single exposure. The multispectral image, corresponding to the light field’s central view, is reconstructed by shifting the spectrally coded subapertures onto the central view according to their respective disparity. We assume that the disparity of the scene is approximately constant and non-zero. Since the spectral mask is identical for all subapertures, the missing spectral data of the central view will be filled up from the shifted spectrally coded subapertures. We investigate the reconstruction quality for different spectral masks and camera parameter sets optimized for real life applications such as in-line production monitoring for which the constant disparity constraint naturally holds. For synthesized reference scenes, using 16 color channels, we achieve a reconstruction PSNRmathrm{PSNR} of up to 51?dB.
机译:我们提出了一种新的方法,可以通过具有频谱编码微透镜阵列的未聚焦的光场相机拍摄的光谱编码光场重建扁平物体的多光谱图像。从这个意义上讲,光谱编码的光场相机用作多光谱快照成像器,在单个曝光中获取多光谱数据库。根据其各自的视差将频谱编码的子孔节转移到中心视图上,通过将频谱编码的子孔节转移到中心视图上来重建多光谱图像。我们假设场景的差异近似恒定和非零。由于频谱掩模对所有子孔节相同,因此将从移位的光谱编码的子孔节填充中心视图的缺失的频谱数据。我们研究了针对现实生活应用优化的不同光谱掩模和相机参数集的重建质量,例如恒定差距约束自然保持的在线生产监测。对于合成参考场景,使用16个色频,我们实现了重建psnr mathrm {psnr}高达51?db。

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