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Spectral bidirectional texture function reconstruction by fusing multiple-color and spectral images

机译:通过融合多色和光谱图像来重建光谱双向纹理函数

摘要

Spectral bidirectional texture function (BTF) is essential for accurate reproduction of material appearance due to its nature of conveying both spatial and spectral information. A practical issue is that the acquisition of raw spectral BTFs is time-consuming. To resolve the limitation, this paper proposes a novel framework for efficient spectral BTF acquisition and reconstruction. The framework acquires red-green-blue (RGB) BTF images and just one spectral image. The full spectral BTFs are reconstructed by fusing the RGB and spectral images based on nonnegative matrix factorization (NMF). Experimental results indicate that the accuracy of spectral reflectance reconstruction is higher than that of existing algorithms. With the reconstructed spectral BTFs, the material appearance can be reproduced with high fidelity under various illumination conditions.
机译:光谱双向纹理函数(BTF)由于其传达空间和光谱信息的特性,对于精确再现材料外观至关重要。一个实际的问题是原始频谱BTF的获取很耗时。为了解决这一局限性,本文提出了一种有效的频谱BTF采集和重建的新框架。该框架获取红绿蓝(RGB)BTF图像和一张光谱图像。通过基于非负矩阵分解(NMF)融合RGB和光谱图像来重建全光谱BTF。实验结果表明,光谱反射率重构的精度高于现有算法。利用重构的光谱BTF,可以在各种照明条件下以高保真度再现材料外观。

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