The aim of this work was to study the spectral characterization of LCD. A spectral characterization model based on RBF neural network was proposed in this paper. The prediction accuracy of model was improved by extending the input variables of neural network. Experimental results showed that introduction of［rg rb gb］item could effectively improve the characterization chromaticity and spectral precision of the model as well as the generalization ability of the network, while introduction of［r2 g2 b2］，［r2 g2 b2］，［rg2 rb2 gr2 gb2 br2 bg2］item could decrease both the characterization precision of the model and the generalization ability of the network. The characterization model with input variable of［r g b rg rb gb］terms of RBF neural network achieved the optimal precision and generalization ability, reaching the colorimetric accuracy of 0.14. Thus, RBF neural network model with input variables of［rg rb gb］was the most optimized model for spectral characterization of LCD with high resolution.