At present, computer color matching is difficult to predict the exact formulation of the problem when color difference formula hours large deviations, so the algorithm is optimized based on the Stearns-Noechel model of the optical model. Using the spectral reflectance data of the two samples were equal and the two samples necessarily colored，and then the discriminant conditions in the computer color matching algorithm program were improved. We Calculated by MATLB, in the interval ［0 1］, every interval of 0.001, the cycle of unknown parameters M value, and selected the full spectrum of the reflectance data when the minimum deviation of the parameter M value to calculate the fit ratio, instead of the minimum color parameters M. The fitting ratio wascalculated and the relative formula deviation of the fitting sample was calculated. The results showed that the average deviation of the average color of the primary color was 0.560 and the secondary color was 0.346 when the deviation of the parameter M was the minimum of the total spectral reflectance data. The minimum deviation of the parameter M was the corresponding formula, the relative deviation of the primary color was 0.723, and the secondary color was 0.383. Compared with the two methods, it can be seen that the relative deviation of the formula after fitting the sample and the standard sample was smaller than the relative formula deviation when the chromatic aberration was minimum. That is, after the optimization of the formula was more close to the real formula, and color accuracy has been significantly improved, helping to reduce the number of late proofing as well as improving color efficiency.