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RISS 인기검색어
- 검색키워드
- 저자 : Leiting Chen (검색결과 2 건)
- 무료
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- 유료
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Realistic Simulation of Incompressible Fluids with Arbitrarily Shaped Boundaries
Xiao Nie,Leiting Chen,Chuan Zhou,Hang Qiu 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.6
We present a particle-based method for realistically modeling the interaction of incompressible fluids with arbitrarily shaped solid boundaries. When dealing with static solids, previous meshless Lagrangian approaches either require uniform sampling of solid boundaries or suffer from unexpected side effects. Our method resolves these issues using a new boundary handling algorithm that represents the solid surface as a single layer of boundary particles with different influence factors. This technique can more efficiently handle arbitrarily shaped boundaries without the side effects of existing approaches, and produces more realistic simulation results. We further propose a new form of weighting kernel that corrects the fluid density estimations and avoids negative pressures at the free surface. We have demonstrated the robustness and effectiveness of our method with a range of scenarios.
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Detail-Enhanced Medical Image Fusion in NSCT Domain
Guocheng Yang,Leiting Chen,Meiling Li 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.8
Multimodal medical image fusion technique plays an important role in clinical applications, such as pathologic diagnosis and surgical options. However, many traditional fusion methods cannot well preserve details of source images in the fused image. To address this problem, a detail-enhanced image fusion scheme based on non-subsampled contourlet transform (NSCT) and gain control (i.e., NCGC) is developed in this paper, which can effectively combine the spectral information and the spatial features of source images. The proposed method applies power law transformation to tune coefficients of each decomposed subband, and adjusts the strength of subband signals by smooth gain control. Eventually, the fused image with more anatomical details and functional information is constructed by the inverse NSCT. Three pairs of medical images with different modalities and three fusion metrics are applied to validate the feasibility of this algorithm. Experimental results demonstrate that the proposed method can achieve superior performance in both visual perception and objective assessment.
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