Abstract:A locally regressive algorithm for color calibration is proposed. Starting from the principle of structural risk minimization, the algorithm regards the residual of total least squares as the empirical risk and chooses the K-nearest neighborhood of a calibration color point to implement local regression for color calibration. Experimental results indicate that the proposed algorithm is superior, in both precision and robustness, to multiple regression and multiple regression based on subspaces and that its average error, maximum error and error standard deviation decrease by 46%(27%), 57%(21%) and 42%(20%) respectively.
丁二锐;王义峰; 曾 平; 丁 阳. 基于结构风险最小化和全最小二乘法的色彩校正[J]. 电子与信息学报, 2008, 30(3): 717-720 .
Ding Er-rui①; Wang Yi-feng①; Zeng Ping①; Ding Yang②. Color Calibration Based on Structural Risk Minimization and Total Least Squares. , 2008, 30(3): 717-720 .