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- 저자 : Hancheng Lu (검색결과 2 건)
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Coupling Effect Diagnoses of Quasi-Stationary Mesoscale Vortex in Guangxi Rainstorm Process of China
Jingjing Ge,Hancheng Lu,Wei Zhong 한국기상학회 2011 Asia-Pacific Journal of Atmospheric Sciences Vol.47 No.1
The mesoscale weather system which affected the Guangxi flash-flood-producing rainstorm of China in June 2008 is a quasistationary mesoscale vortex. Its genesis and development is closely related to the coupling effects of weather systems in different scales and different latitudes. On the one hand, the coupling of synoptic scale high- and low-level jets provides the environmental conditions for development of vortices and vertical circulations in the mesoscale vortex; On the other hand, the coupling of waves in mid-latitude westerlies and perturbations in low-latitude warm-moist flow under the influence of complex terrain makes the mesoscale vortex circulations strengthened. With the piecewise potential vorticity (PV) inversion method, PV anomalies in different regions are analyzed; also the vortex-vortex interactions and vortex-background flow interactions are diagnosed. Thus, the reasons why the mesoscale is quasi-stationary at first, while developing and deepening later are indicated. Under the condition of coupling effects, the vertical motions accompanied with the mesoscale vortex can be diagnosed with the PV-ω inversion system based on the analysis of quasi-balanced flow.
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No-reference Sharpness Index for Scanning Electron Microscopy Images Based on Dark Channel Prior
( Qiaoyue Li ),( Leida Li ),( Zhaolin Lu ),( Yu Zhou ),( Hancheng Zhu ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.5
Scanning electron microscopy (SEM) image can link with the microscopic world through reflecting interaction between electrons and materials. The SEM images are easily subject to blurring distortions during the imaging process. Inspired by the fact that dark channel prior captures the changes to blurred SEM images caused by the blur process, we propose a method to evaluate the SEM images sharpness based on the dark channel prior. A SEM image database is first established with mean opinion score collected as ground truth. For the quality assessment of the SEM image, the dark channel map is generated. Since blurring is typically characterized by the spread of edge, edge of dark channel map is extracted. Then noise is removed by an edge-preserving filter. Finally, the maximum gradient and the average gradient of image are combined to generate the final sharpness score. The experimental results on the SEM blurred image database show that the proposed algorithm outperforms both the existing state-of-the-art image sharpness metrics and the general-purpose no-reference quality metrics.
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