An efficient procedure for spectral reflectance recovery using a new compressive sensing-based spectral sparse recovery method is proposed by using the optimized sparse basis functions to recover spectral reflectance from a single RGB image. Unlike the conventional spectral recovery methods, the sparse basis functions of the proposed method are an optimal solution for obtaining the information needed to consider the characteristics of the RGB response values. The novelty of the proposed method is to obtain the optimized sparse basis functions considering the influence of the spectral reflectance dataset and the sample’s colorimetric characteristic, which meets the minimum of the spectral recovery error. Spectral and colorimetric accuracy of the proposed method is studied to verify the effectiveness compared to existing methods. As the spectral recovery results show, the proposed method is extremely effective in recovering spectral reflectance.

通过使用优化的稀疏基函数从单个 RGB 图像中恢复光谱反射，提出了一种使用新的基于压缩感知的光谱稀疏恢复方法进行光谱反射恢复的有效程序。与传统的光谱恢复方法不同，该方法的稀疏基函数是获取考虑RGB响应值特征所需信息的最佳解决方案。该方法的新颖之处在于获得了考虑光谱反射率数据集和样品色度特性影响的优化稀疏基函数，满足光谱恢复误差最小。研究了所提出方法的光谱和比色精度，以验证与现有方法相比的有效性。