The aim of this work was to use fast independent component analysis to achieve effective utilization of the key technology of colour spectrum information reproducing color accuracy. Fast independent component analysis was applied to munsell colormatt spectroscopy data set for dimension reduction of the space, and the chosen independent components were used to reconstruct spectral space, finally this method was evaluated from the two aspects of accumulated space coverage and colorful accuracy. With the increase of the chosen number of independent components, the cumulative spatial coverage and colorful accuracy data increased gradually. When eight independent components were selected, the cumulative space coverage and colorful precision tended to be steady gradually. According to the demand, five base vectors were selected for accurate color spectrum reconstruction, and eventually the cumulative space coverage reached 97%, the fitting degree of 99.92% of the reconstructed spectrum reached 0.9 and above, the color difference of 100% of samples was less than 0.5. Using fast independent component analysis for dimension reduction of the spectral space could achieve high-precision representation of the original spectral space.