Gaussian Process Transforms

We introduce the Gaussian Process Transform (GPT), an orthogonal transform for signals defined on a finite but otherwise arbitrary set of points in a Euclidean domain. The GPT is obtained as the Karhunen-Loeve Transform MET) of the marginalization of a. Gaussian Process defined on the domain. Compared to the Graph Transform (GT), which is the KLT of a Gauss Markov Random Field over the same set of points whose neighborhood structure is inherited from the Euclidean domain, the GPT has up to 6 dB higher coding gain.