My goal is a more efficient implementation of the algorithm posed in this question.
Consider two sets of points (in N-space. 3-space for the example case of RGB colorsp
To make things more efficient, consider using a Pigeonhole algorithm - group the points in your reference set (your colorTable) by their location in n-space. This allows you to efficiently find the nearest neighbour without having to iterate all the points.
For example, if you were working in 2-space, divide your plane into a 5 x 5 grid, giving 25 squares, with 25 groups of points.
In 3 space, divide your cube into a 5 x 5 x 5 grid, giving 125 cubes, each with a set of points.
Then, to test point n, find the square/cube/group that contains n and test distance to those points. You only need to test points from neighbouring groups if point n is closer to the edge than to the nearest neighbour in the group.