A novel spectrum-extraction method based on a 2-D Gaussian model is proposed in this paper. First, the flat images are employed to fit the model parameters in the spatial orientation and the calibration lamp images are used to fit the model parameters in the wavelength orientation. Then normalized 2-D models are obtained by combining the parameters of the two orientations. The flux-extraction algorithm is based on least-square theory and the 2-D model. Through experiments, the extracted spectra by our method have a stronger ability to reduce noise than the 1-D spectrum extraction method.