  Through optimization we can solve for a filter that when the camera views the
world through this filter, it is more colorimetric. Previous work solved for
the filter that best satisfied the Luther condition: the camera spectral
sensitivities after filtering were approximately a linear transform from the
CIE XYZ color matching functions. A more recent method optimized for the filter
that maximized the Vora-Value (a measure which relates to the closeness of the
vector spaces spanned by the camera sensors and human vision sensors). The
optimized Luther- and Vora-filters are different from one another.
  In this paper we begin by observing that the function defining the Vora-Value
is equivalent to the Luther-condition optimization if we use the orthonormal
basis of the XYZ color matching functions, i.e. we linearly transform the XYZ
sensitivities to a set of orthonormal basis. In this formulation, the
Luther-optimization algorithm is shown to almost optimize the Vora-Value.
Moreover, experiments demonstrate that the modified orthonormal Luther-method
finds the same color filter compared to the Vora-Value filter optimization.
Significantly, our modified algorithm is simpler in formulation and also
converges faster than the direct Vora-Value method.

Computer Vision and Pattern Recognition