基于单幅多光谱图像的照明光谱估计方法

Illumination Spectrum Estimation Method Based on Single Multispectral Image

由于场景的光谱信息受到不同照明条件的影响,故在照明不可控场景下拍摄的多光谱图像的光谱反射比重构需要进行照明光谱估计。因此,提出了一种基于单幅多光谱图像的通用方法来准确预测场景的照明光谱。首先,通过分析每个像素的响应特性设计并计算色度权重图,以寻找包含更多照明信息的像素。然后,对加权后的图像进行成分分析,以在通道域中提取光源响应特征。最后,得益于创新性引入的基于照明光谱库训练的字典学习方法,可估计出场景光源的相对光谱功率分布。所提方法在模拟数据和真实数据上的照明光谱估计平均角度误差分别为0.29和3.42,与现有的同类方法相比,表现出更优的准确性和鲁棒性。

The spectral information of the scene is affected by different illumination conditions,hence the spectral reflectance reconstruction of multispectral images taken under scenes with uncontrollable illumination requires illumination spectrum estimation.Therefore,a general method based on a single multispectral image is proposed to accurately predict the illumination spectrum of the scene.First,by analyzing the response features of each pixel,the chroma weight map is designed and calculated to find the pixels that contain more illumination information.Then,the component analysis of the weighted image is carried out to extract the illuminant response features in the channel domain.Finally,benefiting from the innovative introduction of the dictionary learning method trained by illumination spectrum library,the relative spectral power distribution of the scene illuminant can be estimated.The average angular errors of the illumination spectrum estimation obtained by the proposed method on simulated data and real data are 0.29 and 3.42,respectively.Compared with the existing counterparts,the proposed method shows better accuracy and robustness.