The aim of this work was to study the accuracy of the image spectral reflectance reconstructed based on BP neural network and FNN neural network. SG standard color card was taken as the training sample to predict the spectral reflectance of DC standard color card using BP neural network and FNN neural network, respectively, and then the results were evaluated and analyzed with CIE L*a*b* color difference, error root mean square and Goodness-Fitting Coefficient. The average color difference, average error root mean and average Goodness-Fitting Coefficient of reflectance reconstructed with BP neural network were 2.997, 0.056, and 0.981, respectively, while those reconstructed with FNN neural network were 3.071, 0.049, and 0.991, respectively. The spectral reflectance reconstructed by both neural networks had good color and spectral accuracy. Compared to the FNN neural network, BP neural network was more suitable for the field of spectral image acquisition.