基于低密度奇偶校验码的计算鬼成像
Computational Ghost Imaging with Low-Density Parity-Check Code
AI总结：
针对复杂环境下如何利用信息冗余提高鬼成像可信度的问题，提出基于LDPC编码辐射场的计算GI系统，建立匹配衰落信道模型消除非理想因素，推导误码率下界并经实验验证其有效性与性能。
摘要：
鬼成像（GI）是一种高分辨率成像技术，在过去20年中一直受到许多领域的关注。大多数GI研究者关注欠采样信号的重构，然而，如何利用信息冗余来提高复杂环境中结果的可信度却鲜有研究。受此启发，我们通过利用信号冗余，提出了一种基于低密度奇偶校验（LDPC）编码辐射场的计算GI系统。通过建立匹配的衰落信道模型，可以消除成像过程中产生的非理想因素。我们推导了所提出的LDPC编码GI系统的误码率解析下界。通过数值和实验结果，进一步验证了LDPC编码GI系统的有效性和性能。
英文摘要：
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.
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