3D point cloud to 2.5D graycale image (metric) [Halcon?]
Your 3 channels already give you the 3D coordinates, and from that 3 images, you already know which pixels locations the 3D data are projected. So you don't need to do anything. If you like to get a depth image, just set:
$$
depth(i,j) = z(i,j)
$$
In Halcon, you just select the Z-channel using access_channel.
If you desire a distance image, then:
$$
distance(i,j) = \lVert (x,y,z)^T \rVert
$$
The norm defines the distance metric you would like to use. Traditionally, I would say Euclidean $\|\cdot\|=\sqrt{x^2+y^2+z^2}$. You could do this in any language by using operations like addition, multiplication and square roots.