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Signal-to-Noise Comparison of Deconvolution From Wave Front Sensing With Traditional Linear and Speckle Image Reconstruction

机译：波前传感反卷积与传统线性和散斑图像重建的信噪比

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Byron M. Welsh; Michael C. Roggemann;
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年度 2007
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1. SIGNAL-TO-NOISE COMPARISON OF DECONVOLUTION FROM WAVE-FRONT SENSING WITH TRADITIONAL LINEAR AND SPECKLE IMAGE RECONSTRUCTION [J] . Welsh BM., Roggemann MC. Applied optics . 1995,第12期

机译：传统线性和斑点图像重建的波前传感反卷积信噪比较
2. Experimental measurements of estimator bias and the signal-to-noise ratio for deconvolution from wave-front sensing [J] . David Dayton, John Gonglewski, Samuel Rogers Applied optics . 1997,第16a18期

机译：从波前感测反卷积的估计器偏差和信噪比的实验测量
3. Experimental measurements of estimator bias and the signal-to-noise ratio for deconvolution from wave-front sensing [J] . Dayton D, Gonglewski J, Rogers S, Applied optics . 1997,第17期

机译：从波前感测反卷积的估计器偏差和信噪比的实验测量
4. A. comparison of multi-frame blind deconvolution and speckle imaging energy spectrum signal-to-noise ratios [C] . Charles L. Matson SPIE Conference on Optics in Atmospheric Propagation and Adaptive Systems . 2008

机译：A.多帧盲卷积和斑点成像能谱信噪比的比较
5. Comparison of speckle noise reduction techniques using near shift invariant wavelet transforms with application to SAR imagery. [D] . Kirpalani, Ashwin L. 2009

机译：使用近移不变小波变换的斑点降噪技术的比较及其在SAR图像中的应用。
6. Wave front analysis for enhanced time-domain beamforming of point-like targets in optoacoustic imaging using a linear array [O] . Marc Fournelle, Wolfgang Bost 2019

机译：波前分析可增强线性阵列在光声成像中点状目标的时域波束形成
7. Maximum Likelihood Deconvolution of Beamformed Images with Signal-Dependent Speckle Fluctuations from Gaussian Random Fields: With Application to Ocean Acoustic Waveguide Remote Sensing (OAWRS) [O] . Ankita D. Jain, Nicholas C. Makris 2016

机译：高斯随机场中具有信号相关散斑波动的波束形成图像的最大似然反褶积：应用于海洋声波波导遥感（OaWRs）
8. Comparison of Multi-Frame Blind Deconvolution and Speckle Imaging Energy Spectrum Signal-to-Noise Ratios (Preprint); Conference paper [R] . Matson, C. L. 2008

机译：多帧盲解卷积和散斑成像能谱信噪比的比较（预印本）;会议文件

Signal-to-Noise Comparison of Deconvolution From Wave Front Sensing With Traditional Linear and Speckle Image Reconstruction

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