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An iterative wavefront sensing algorithm for high-contrast imaging systems 被引量:4
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作者 Jiang-Pei Dou 1,2,De-Qing Ren 1,2,3 and Yong-Tian Zhu 1,2 1 National Astronomical Observatories/Nanjing Institute of Astronomical Optics & Technology,Chinese Academy of Sciences,Nanjing 210042,China 2 Key Laboratory of Astronomical Optics & Technology,Nanjing Institute of Astronomical Optics & Technology,Chinese Academy of Sciences,Nanjing 210042,China 3 Physics & Astronomy Department,California State University Northridge,18111 Nordhoff Street,Northridge,California 91330-8268,USA 《Research in Astronomy and Astrophysics》 SCIE CAS CSCD 2011年第2期198-204,共7页
Wavefront sensing from multiple focal plane images is a promising technique for high-contrast imaging systems.However,the wavefront error of an optics system can be properly reconstructed only when it is very small.Th... Wavefront sensing from multiple focal plane images is a promising technique for high-contrast imaging systems.However,the wavefront error of an optics system can be properly reconstructed only when it is very small.This paper presents an iterative optimization algorithm for the direct measurement of large static wavefront errors from only one focal plane image.We first measure the intensity of the pupil image to get the pupil function of the system and acquire the aberrated image on the focal plane with a phase error that will be measured.Then we induce a dynamic phase on the tested pupil function and calculate the associated intensity of the reconstructed image on the focal plane.The algorithm will then try to minimize the intensity difference between the reconstructed image and the aberrated test image in the focal plane,where the induced phase is a variable of the optimization algorithm.The simulation shows that the wavefront of an optical system can theoretically be reconstructed with high precision,which indicates that such an iterative algorithm may be an effective way to perform wavefront sensing for high-contrast imaging systems. 展开更多
关键词 techniques: image processing -- methods: numerical -- planetarysystems
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Effects of mesh style and grid convergence on numerical simulation accuracy of centrifugal pump 被引量:2
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作者 刘厚林 刘明明 +1 位作者 白羽 董亮 《Journal of Central South University》 SCIE EI CAS CSCD 2015年第1期368-376,共9页
In order to evaluate the effects of mesh generation techniques and grid convergence on pump performance in centrifugal pump model, three widely used mesh styles including structured hexahedral, unstructured tetrahedra... In order to evaluate the effects of mesh generation techniques and grid convergence on pump performance in centrifugal pump model, three widely used mesh styles including structured hexahedral, unstructured tetrahedral and hybrid prismatic/tetrahedral meshes were generated for a centrifugal pump model. And quantitative grid convergence was assessed based on a grid convergence index(GCI), which accounts for the degree of grid refinement. The structured, unstructured or hybrid meshes are found to have certain difference for velocity distributions in impeller with the change of grid cell number. And the simulation results have errors to different degrees compared with experimental data. The GCI-value for structured meshes calculated is lower than that for the unstructured and hybrid meshes. Meanwhile, the structured meshes are observed to get more vortexes in impeller passage.Nevertheless, the hybrid meshes are found to have larger low-velocity area at outlet and more secondary vortexes at a specified location than structured meshes and unstructured meshes. 展开更多
关键词 mesh style grid convergence index(GCI) numerical simulation particle image velocimetry(PIV) centrifugal pump
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Fast compression and reconstruction of astronomical images based on compressed sensing
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作者 Wang-Ping Zhou Yang Li +2 位作者 Qing-Shan Liu Guo-Dong Wang Yuan Liu 《Research in Astronomy and Astrophysics》 SCIE CAS CSCD 2014年第9期1207-1214,共8页
With the fast increase in the resolution of astronomical images, the question of how to process and transfer such large images has become a key issue in astronomy. We propose a new real-time compression and fast recon... With the fast increase in the resolution of astronomical images, the question of how to process and transfer such large images has become a key issue in astronomy. We propose a new real-time compression and fast reconstruction algorithm for astronomical images based on compressive sensing techniques. We first reconstruct tile Original signal with fewer measurements, according to its compressibility. Then, based on the characteristics of astronomical images, we apply Daubechies orthogonal wavelets to obtain a sparse representation. A matrix representing a random Fourier ensembleis used to obtain a sparse representation in a lower dimensional space. For reconstructing the image, we propose a novel minimum total variation with block addptive sensing to balance the accuracy and eomputation time. Our experimental results show that the proposed algorithm can efficiently reconstruct colorful astronomicai images with high resolution and improve the applicability of compressed sensing. 展开更多
关键词 methods: data analysis -- methods: numerical -- techniques: image processing
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