压缩传感
多模光纤
偏移量(计算机科学)
计算机科学
纤维
高斯分布
光学
光纤
材料科学
算法
电信
物理
量子力学
复合材料
程序设计语言
作者
Qi Qin,Yan Liu,Tan Zhang,Muguang Wang,Fengping Yan
出处
期刊:Optik
[Elsevier]
日期:2020-10-01
卷期号:220: 164783-164783
被引量:1
标识
DOI:10.1016/j.ijleo.2020.164783
摘要
Compressive sensing (CS) is a recently developed theory which allows reconstruction of sparse signals with the number of measurements much lower than that required by the Nyquist sampling, and sensing the signals with a measurement matrix (MM) is one of the indispensable key procedures. Based on the specklegrams of multimode fiber (MMF) with offset-launching and coreless multimode fiber (CMF) with center-launching, MM was constructed and applied in CS. The constructed MMs provide improved performances compared with the conventional Gaussian MM in CS when applied to image reconstruction. Specklegrams of MMF with different launching offsets and CMF with different wavelengths were respectively used to construct the MMs by different construction methods, which demonstrated the flexibility of the combination of fiber specklegrams to get a MM. By careful comparisons, it can be concluded that MMs based on the fiber specklegrams perform better in providing a good Peak Signal to Noise Ratio. Moreover, the construction methods can be easily implemented, which is highly promising for compressive sensing.
科研通智能强力驱动
Strongly Powered by AbleSci AI