Computational Ghost Imaging with Low-Density Parity-Check Code

TL;DR

This paper introduces a novel computational ghost imaging system that leverages low-density parity-check (LDPC) codes to utilize signal redundancy, improving image reconstruction in complex environments.

Contribution

It proposes a new LDPC-coded ghost imaging system that exploits signal redundancy and models non-ideal factors to enhance imaging performance.

Findings

Derived analytical lower bound on bit error rate.

Validated system effectiveness through numerical simulations.

Confirmed improved imaging results experimentally.

Abstract

Ghost imaging (GI) is a high-resolution imaging technology that has been a subject of interest to many fields in the past 20 years. Most GI researchers focus on the reconstruction of signal under-sampling, nevertheless, how to use information redundancy to improve the result's belief in a complex environment has hardly been studied. Motivated by this, we propose a computational GI system based on the low-density parity-check (LDPC) coded radiation field by exploiting the signal redundancy. The non-ideal factors generated within the imaging process can be eliminated by setting up the matching fading channel model. We have derived the analytical lower bound on the bit error rate for the proposed LDPC-coded GI system. The effectiveness and performance of the LDPC-coded GI system are further validated through numerical and experiment results.