Detecting Markov Random Fields Hidden in White Noise

Abstract

Motivated by change point problems in time series and the detection of textured objects in images, we consider the problem of detecting a piece of a Gaussian Markov random field hidden in white Gaussian noise. We derive minimax lower bounds and propose near-optimal tests.

In the 2nd version we removed the part on path detection, which will appear on its own in a separate paper