Compressive imaging using fast transform coding

TL;DR

This paper introduces deterministic sampling strategies for compressive imaging using Delsarte-Goethals frames, enabling multi-scale measurements linked to Haar wavelet transforms, and demonstrates their effectiveness through numerical experiments.

Contribution

The paper presents a novel deterministic sampling approach for compressive imaging based on Delsarte-Goethals frames, connecting measurements to Haar wavelet scales.

Findings

Effective multi-scale measurements demonstrated

Sampling strategies outperform random methods in experiments

Measurements relate to Haar wavelet transform

Abstract

We propose deterministic sampling strategies for compressive imaging based on Delsarte-Goethals frames. We show that these sampling strategies result in multi-scale measurements which can be related to the 2D Haar wavelet transform. We demonstrate the effectiveness of our proposed strategies through numerical experiments.