Modeling Signals Embedded in a Euclidean Domain

  • Philip A. Chou ,
  • Ricardo L. de Queiroz ,
  • Philip A. Chou

Graph Signal Processing (GSP) |

Graphs are often used to model signals defined on a set of points embedded in a Euclidean domain. Examples are distributed sensor readings, measures of congestion in a transportation network, samples in a feature space, and colors on a 3D point clouds. However, it may be better to model such signals as samples of a Gaussian Process defined on the Euclidean domain. We show, on a 3D point cloud example, that Karhunen Loeve Transforms (KLTs) based on Gaussian Process models can have significantly higher energy compaction and coding gain than KLTs based on sparse graph models. The latter KLTs are known as Graph Transforms; we call the former Gaussian Process Transforms.