Spectral reflectance is sparse in space, and while the traditional spectral-reconstruction algorithm doesnot make full use of this characteristic sparseness, the compressive sensing algorithm can make full useof it. In this paper, on the basis of analyzing compressive sensing based on the orthogonal matching pursuitalgorithm, a new algorithm based on the Dice matching criterion is proposed. The Dice similarity coefficientis introduced, to calculate the correlation coefficient of the atoms and the residual error, and is used toselect the atoms from a library. The accuracy of Spectral reconstruction based on the pseudo-inversemethod, Wiener estimation method, OMP algorithm, and DOMP algorithm is compared by simulation onthe MATLAB platform and experimental testing. The result is that spectral-reconstruction accuracy basedon the DOMP algorithm is higher than for the other three methods. The root-mean-square error and colordifference decreases with an increasing number of principal components. The reconstruction error decreasesas the number of iterations increases. Spectral reconstruction based on the DOMP algorithm can improvethe accuracy of color-information replication effectively, and high-accuracy color-information reproductioncan be realized.