基于编码复用的多光谱鬼成像研究进展

Research progresses of code-multiplexing multispectral ghost imaging

基于编码复用的多光谱鬼成像(multispectral ghost imaging,MGI)是一种新型成像技术,其通过巧妙设计的编解码策略,显著提升了光谱成像性能,具有简单化和智能化的特点。从MGI的基本原理和关键技术出发,详细探讨了多种编码复用策略及其重构算法,主要包括基于随机散斑、Hadamard散斑和傅里叶散斑的编码复用策略,以及相应的重构算法,如压缩感知、傅里叶逆变换和深度学习等。这些方案在提取目标场景的空间结构及光谱特性时各具特色,展现了不同的成像优势和适用场景。然而,MGI技术仍存在投影效率低、计算复杂度高等挑战,未来有望通过更高效的图像重建算法、智能化技术及先进光学器件,进一步提升MGI系统的成像性能,以满足复杂场景的高质量成像需求。

Multispectral ghost imaging(MGI)based on code-multiplexing is a novel imaging technology that significantly enhances spectral imaging performance through cleverly designed encoding and decoding strategies,characterized by simplification and intelligence.This paper starts from the fundamental principles and key technologies of the MGI and thoroughly explores various coding multiplexing strategies and their reconstruction algorithms,primarily including coding multiplexing strategies based on random patterns,Hadamard patterns,and Fourier patterns,as well as corresponding reconstruction algorithms such as compressed sensing,Fourier inverse transform,and deep learning.These approaches exhibit unique characteristics in extracting the spatial structure and spectral properties of the target scene,showing different imaging advantages and applicable scenarios.However,the technique still faces challenges such as low projection efficiency and high computational complexity.In the future,it is expected to further improve the imaging performance of the MGI system through more efficient image reconstruction algorithms,intelligent technologies and advanced optics to meet the high-quality imaging needs of complex scenes.