Single-pixel cameras, which employ either structured illumination or image modulation and compressive sensing algorithms, provide an alternative approach to imaging in scenarios where the use of a detector array is re...Single-pixel cameras, which employ either structured illumination or image modulation and compressive sensing algorithms, provide an alternative approach to imaging in scenarios where the use of a detector array is restricted or difficult because of cost or technological constraints. In this work, we present a robust imaging method based on compressive imaging that sets two thresholds to select the measurement data for image reconstruction. The experimental and numerical simulation results show that the proposed double-threshold compressive imaging protocol provides better image quality than previous compressive imaging schemes. Faster imaging speeds can be attained using this scheme because it requires less data storage space and computing time. Thus, this denoising method offers a very effective approach to promote the implementation of compressive imaging in real-time practical applications.展开更多
基金supported by the National Natural Science Foundation of China(Nos.11675014,61605218,61601442,61575207,and 61474123)the National Major Scientific Instruments Development Project of China(No.2013YQ030595)+2 种基金the National Defense Science and Technology Innovation Foundation of Chinese Academy of Sciences,the Science and Technology Innovation Foundation of Chinese Academy of Sciences(No.CXJJ-16S047)the Program of International Science and Technology Cooperation(No.2016YFE0131500)the Advance Research Project(No.30102070101)
文摘Single-pixel cameras, which employ either structured illumination or image modulation and compressive sensing algorithms, provide an alternative approach to imaging in scenarios where the use of a detector array is restricted or difficult because of cost or technological constraints. In this work, we present a robust imaging method based on compressive imaging that sets two thresholds to select the measurement data for image reconstruction. The experimental and numerical simulation results show that the proposed double-threshold compressive imaging protocol provides better image quality than previous compressive imaging schemes. Faster imaging speeds can be attained using this scheme because it requires less data storage space and computing time. Thus, this denoising method offers a very effective approach to promote the implementation of compressive imaging in real-time practical applications.
