Iterative deconvolution methods for ghost imaging
Situ, Guohai; Wang, Wei
2016
通讯作者wangweihust@126.com ; ghsitu@siom.ac.cn
英文摘要Ghost imaging (GI) is an important technique in single-pixel imaging. It has been demonstrated that GI has applications in various areas such as imaging through harsh environments and optical encryption. Correlation is widely used to reconstruct the object image in GI. But it only offers the signal-to-noise ratios(SNR) of the reconstructed image linearly proportional to the number of measurements. Here, we develop a kind of iterative deconvolution methods for GI. With the known image transmission matrix in GI, the first one uses an iterative algorithm to decrease the error between the reconstructed image and the ground-truth image. Ideally, the error converges to a minimum for speckle patterns when the number of measurements is larger than the number of resolution cells. The second technique, Gerchberg-Saxton (GS) like GI, takes the advantage of the integral property of the Fourier transform, and treats the captured data as constraints for image reconstruction. According to this property, we can regard the data recorded by the bucket detector as the Fourier transform of the object image evaluated at the origin. Each of the speckle patterns randomly selects certain spectral components of the object and shift them to the origin in the Fourier space. One can use these constraints to reconstruct the image with the GS algorithm. This deconvolution method is suitable for any single pixel imaging models. Compared to conventional GI, both techniques offer a nonlinear growth of the SNR value with respect to the number of measurements.
会议录OPTOELECTRONIC IMAGING AND MULTIMEDIA TECHNOLOGY IV
语种英语
ISSN号0277-786X
内容类型会议论文
源URL[http://ir.siom.ac.cn/handle/181231/27443]  
专题上海光学精密机械研究所_信息光学与光电技术实验室
作者单位中国科学院上海光学精密机械研究所
推荐引用方式
GB/T 7714
Situ, Guohai,Wang, Wei. Iterative deconvolution methods for ghost imaging[C]. 见:.
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