Bayesian estimation of device spectral sensitivities and its application to improvement of color accuracy using color balancing filter

摘要

We proposed a Bayesian method for estimating the system spectral sensitivities of a color imaging device such as a scanner and a camera from an acquired color chart image. The system sensitivities are defined by the product of spectral sensitivities of camera and spectral power distribution of illuminant, and characterize color separation. In addition we proposed a scheme for predicting the optimal filter to increase color accuracy of the device based on the estimated sensitivities. The predicted filter is attached to the front of camera and modifies the system spectral sensitivities. This study aimed to improve color reproduction of the imaging device in practical way even if the spectral sensitivities of the device are unknown. The proposed method is derived by introducing the non-negativity, the smoothness and the zero boundaries of the sensitivity curves as prior information. All hyperparameters in the proposed Bayesian model can be determined automatically by the marginalized likelihood criterion. The modified system sensitivities and their color accuracy are predicted computationally. An experiment was carried out to test the performance of the proposed method for predicting the color accuracy improvement using two scanners. The average color difference was reduced from 3.07 to 2.04 and from 2.11 to 1.77 in the two scanners.