Recently, Cao et al proposed an adaptive weighting method for the training samples for reflectance reconstruction according to both colorimetric and spectral reflectance similarities for a given vector defined by tristimulus values. It was shown the Cao et al method outperforms the other methods including the regression estimation method in terms of multiple evaluation criteria. In this article, motivated by the work of Cao et al, a hybrid weight is introduced, which results in the size of the training samples selected is half of that used by the Cao et al method. Simulation results showed that the proposed method performs equally well as or slightly better than the Cao et al method, but uses less central processing unit time than that used by the Cao et al method. It was also found that about 100 training samples selected is good enough for the proposed method.