苏州大学光电科学与工程学院，江苏 苏州 215006
通过测量矩阵获取Gram矩阵，梳理了Gram矩阵与系统点扩散函数的关系，进而基于点扩散函数提出最强旁瓣峰值大小、叠加旁瓣峰值大小、空间距离和频谱余弦相似度4个特征参量。在此基础上，构建了一种单像素压缩成像高质量图像重建的特征函数，建立了可重建的目标稀疏度与特征函数的关系，并通过数值模拟和实验验证了所提特征函数的有效性，该工作对于单像素成像系统测量矩阵的优化设计具有重要借鉴意义。
成像系统 单像素成像 压缩感知 测量矩阵 特征函数
Author Affiliations
Abstract
1 School of Optoelectronic Science and Engineering, Soochow University, Suzhou 215006, China
2 Key Laboratory of Modern Optical Technologies of the Ministry of Education, Soochow University, Suzhou 215006, China
The source’s energy fluctuation has a great effect on the quality of single-pixel imaging (SPI). When the method of complementary detection is introduced into an SPI camera system and the echo signal is corrected with the summation of the light intensities recorded by two complementary detectors, we demonstrate, by both experiments and simulations, that complementary single-pixel imaging (CSPI) is robust to the source’s energy fluctuation. The superiority of the CSPI structure is also discussed in comparison with previous SPI via signal monitoring.
computational imaging image reconstruction complementary detection correlation function Chinese Optics Letters
2024, 22(3): 031101
