外文题目: Iterative deconvolution methods for ghost imaging
作者: Wang, Wei; Situ, Guohai
刊名: Proc.SPIE
来源图书: OPTOELECTRONIC IMAGING AND MULTIMEDIA TECHNOLOGY IV
年: 2016 卷: 10020 文章编号：1002004
会议名称: Conference on Optoelectronic Imaging and Multimedia Technology IV
英文关键词:
Ghost imaging; image processing; signal to noise ratio
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.


文献类型: 会议论文
正文语种: English
收录类别: ISTP
DOI: 10.1117/12.2246122


全文传递服务