Study on spectral adaptive transformation based on chromatic aberration

The spectral reflectance of multispectral images can provide more valuable information about object characteristics. In order to improve the utilization of the spectrum, the reflectance reconstruction requires the same system calibration and illumination of the image acquisition. Therefore, Khan proposed the concept of multispectral constancy, which is to transform the multispectral image data into a standard representation through spectral adaptive transformation. Khan used the linear mapping method to solve SAT to convert the multispectral image data obtained under unknown illumination into the image data under standard light source. In order to further improve the spectral utilization rate and expand the application range of multispectral cameras, an algorithm to improve multispectral constancy based on chromatic aberration index is proposed in this paper. The algorithm uses chromatic aberration as the objective function to solve the spectral adaptive transformation. In this paper, ten light sources are used as unknown light sources, SFU and X-rite are used as training and testing datasets, and multispectral camera channels are simulated by Equi-Gaussian and Equi-Energy filters with different number of channels to train and test 5, 6, 8, and 10 channels of data. In this paper, the color difference under different light sources is used as the evaluation index to test the performance of the proposed algorithm, and compared with the Khan method for calculating SAT multispectral constancy. The experimental results show that the spectral constancy algorithm based on color difference can perform better, and expand the application of different kinds of unknown light sources in multispectral constancy.