Spectral reflectance is sparse in space, and while the traditional
spectral-reconstruction algorithm does not make full use of this
characteristic sparseness, the compressive sensing algorithm can make full
use of it. In this paper, on the basis of analyzing compressive sensing
based on the orthogonal matching pursuit algorithm, a new algorithm based
on the Dice matching criterion is proposed. The Dice similarity
coefficient is introduced, to calculate the correlation coefficient of the
atoms and the residual error, and is used to select the atoms from a
library. The accuracy of Spectral reconstruction based on the
pseudo-inverse method, Wiener estimation method, OMP algorithm, and DOMP
algorithm is compared by simulation on the MATLAB platform and
experimental testing. The result is that spectral-reconstruction accuracy
based on the DOMP algorithm is higher than for the other three methods.
The root-mean-square error and color difference decreases with an
increasing number of principal components. The reconstruction error
decreases as the number of iterations increases. Spectral reconstruction
based on the DOMP algorithm can improve the accuracy of color-information
replication effectively, and high-accuracy color-information reproduction
can be realized.
© 2016 Optical Society of Korea
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