Skin spectral reflectance is playing an increasingly important role in many fields, including medical diagnosis, computer graphics, cosmetics industry, and even social sciences. In this paper, we proposed an algorithm based on multispectral imaging to reconstruct the skin spectral reflectance. Polynomial regression model, the equi-Gaussian filters and the equienergy filters were employed in the proposed algorithm. The performance of the proposed algorithm was evaluated under different numbers of filters and noise based on the chromatic aberration (ΔE) under D65 light source, and compared with the other spectral reconstruction algorithms appeared in previous literatures. What’s more, the real human skin datasets were employed to reconstruct the skin spectrum, which made our research more practical. According to the reconstruction results of the real skin data set, the proposed algorithm leads to considerable improvements in comparison with other algorithms.
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