BCH Coding Assisted Imaging

TL;DR

This paper presents a novel method that integrates BCH error control coding into ghost imaging systems to enhance image quality and robustness under noisy conditions, validated through simulations and experiments.

Contribution

It introduces the use of BCH ECC with order-statistic decoding in correlation imaging, improving robustness and image fidelity in low-light or noisy environments.

Findings

BCH coding significantly improves image reconstruction quality.

The approach enhances robustness against Gaussian noise.

Different BCH codes offer varying performance benefits.

Abstract

In modern correlation imaging systems, also known as ghost imaging (GI), particularly under low-light or noisy conditions, preserving high image fidelity presents a significant challenge. This paper introduces an innovative approach by integrating Bose-Chaudhuri-Hocquenghem (BCH) error control coding (ECC) into CGI systems to assist imaging. By encoding target image with BCH codes and using order-statistic decoding (OSD) for error correction during reconstruction, this approach significantly improves image quality across various signal-to-noise ratio (SNR) conditions. Simulation and experiment results validate that BCH coding assisted imaging achieves significantly enhanced robustness against additive white Gaussian noise (AWGN) and improved image reconstruction quality. In addition, the imaging performance of different BCH codes varies, with each code exhibiting distinct advantages based on factors such as code length and coding efficiency.