  Measuring the physical properties of galaxies such as redshift frequently
requires the use of Spectral Energy Distributions (SEDs). SED template sets
are, however, often small in number and cover limited portions of photometric
color space. Here we present a new method to estimate SEDs as a function of
color from a small training set of template SEDs. We first cover the
mathematical background behind the technique before demonstrating our ability
to reconstruct spectra based upon colors and then compare to other common
interpolation and extrapolation methods. When the photometric filters and
spectra overlap we show reduction of error in the estimated spectra of over 65%
compared to the more commonly used techniques. We also show an expansion of the
method to wavelengths beyond the range of the photometric filters. Finally, we
demonstrate the usefulness of our technique by generating 50 additional SED
templates from an original set of 10 and applying the new set to photometric
redshift estimation. We are able to reduce the photometric redshifts standard
deviation by at least 22.0% and the outlier rejected bias by over 86.2%
compared to original set for z $\leq$ 3.
