Detection of Geometric Structures by an Optimally Subsampled Shearlet System in Noisy Digital Images

Abstract

We provide a statistical analysis of the ability of digitized continuous shearlet systems to detect objects embedded in white noise. We analyze the possibility to subsample the shearlet transform and obtain a subset of significantly reduced cardinality that can still yield statistically optimal detection results.