分析了二维非稳定场的可视化方法(Unsteady flow Line Integral Convolution,UFLIC),并针对其产生每帧图像费时较多的缺陷,进行了改进。采用弹性算法来控制种子的释放,通过重用、复制相关迹线来减少迹线的积分计算,达到减少生成每帧图...分析了二维非稳定场的可视化方法(Unsteady flow Line Integral Convolution,UFLIC),并针对其产生每帧图像费时较多的缺陷,进行了改进。采用弹性算法来控制种子的释放,通过重用、复制相关迹线来减少迹线的积分计算,达到减少生成每帧图像所需的时间的效果。实验证明在生成的图像质量相当的前提下,种子控制算法比UFLIC算法更快。展开更多
Line integral convolution(LIC)is a useful visualization technique for a vector field.However,the output image produced by LIC has many problems in a marine vector field.We focus on the visual quality improvement when ...Line integral convolution(LIC)is a useful visualization technique for a vector field.However,the output image produced by LIC has many problems in a marine vector field.We focus on the visual quality improvement when LIC is applied in the ocean steady and unsteady flow field in the following aspects.When a white noise is used as the input in a steady flow field,interpolation is used to turn the discrete white noise into continuous white noise to solve the problem of discontinuity.The"cross"high-pass filtering is used to enhance the textures of streamlines to be more concentrated and continuity strengthened for each streamline.When a sparse noise is used as the input in a steady flow field,we change the directions of background sparse noise according to the directions of vector field to make the streamlines clearer and brighter.In addition,we provide a random initial phase for every streamline to avoid the pulsation effect during animation.The velocities of vector field are encoded in the speed of the same length streamlines so that the running speed of streamlines can express flow rate.Meanwhile,to solve the problem of obvious boundaries when stitching image,we change the streamline tracking constraints.When a white noise is used as an input in an unsteady flow field,double value scattering is used to enhance the contrast of streamlines;moreover,the"cross"high-pass filtering is also adopt instead of two-dimensional high-pass filtering.Finally,we apply the above methods to a case of the surface wave field in typhoon condition.Our experimental results show that applying the methods can generate high-quality wave images and animations.Therefore,it is helpful to understand and study waves in typhoon condition to avoid the potential harm of the waves to people's lives and property.展开更多
Geographic visualization is essential for explaining and describing spatiotemporal geographical processes in flow fields.However,due to multi-scale structures and irregular spatial distribution of vortices in complex ...Geographic visualization is essential for explaining and describing spatiotemporal geographical processes in flow fields.However,due to multi-scale structures and irregular spatial distribution of vortices in complex geographic flow fields,existing two-dimensional visualization methods are susceptible to the effects of data accuracy and sampling resolution,resulting in incomplete and inaccurate vortex information.To address this,we propose an adaptive Line Integral Convolution(LIC)based geographic flow field visualization method by means of rotation distance.Our novel framework of rotation distance and its quantification allows for the effective identification and extraction of vortex features in flow fields effectively.We then improve the LIC algorithm using rotation distance by constructing high-frequency noise from it as input to the convolution,with the integration step size adjusted.This approach allows us to effectively distinguish between vortex and non-vortex fields and adaptively represent the details of vortex features in complex geographic flow fields.Our experimental results show that the proposed method leads to more accurate and effective visualization of the geographic flow fields.展开更多
文摘分析了二维非稳定场的可视化方法(Unsteady flow Line Integral Convolution,UFLIC),并针对其产生每帧图像费时较多的缺陷,进行了改进。采用弹性算法来控制种子的释放,通过重用、复制相关迹线来减少迹线的积分计算,达到减少生成每帧图像所需的时间的效果。实验证明在生成的图像质量相当的前提下,种子控制算法比UFLIC算法更快。
基金Supported by the National Key Research and Development Program of China(No.2016YFC1402000)
文摘Line integral convolution(LIC)is a useful visualization technique for a vector field.However,the output image produced by LIC has many problems in a marine vector field.We focus on the visual quality improvement when LIC is applied in the ocean steady and unsteady flow field in the following aspects.When a white noise is used as the input in a steady flow field,interpolation is used to turn the discrete white noise into continuous white noise to solve the problem of discontinuity.The"cross"high-pass filtering is used to enhance the textures of streamlines to be more concentrated and continuity strengthened for each streamline.When a sparse noise is used as the input in a steady flow field,we change the directions of background sparse noise according to the directions of vector field to make the streamlines clearer and brighter.In addition,we provide a random initial phase for every streamline to avoid the pulsation effect during animation.The velocities of vector field are encoded in the speed of the same length streamlines so that the running speed of streamlines can express flow rate.Meanwhile,to solve the problem of obvious boundaries when stitching image,we change the streamline tracking constraints.When a white noise is used as an input in an unsteady flow field,double value scattering is used to enhance the contrast of streamlines;moreover,the"cross"high-pass filtering is also adopt instead of two-dimensional high-pass filtering.Finally,we apply the above methods to a case of the surface wave field in typhoon condition.Our experimental results show that applying the methods can generate high-quality wave images and animations.Therefore,it is helpful to understand and study waves in typhoon condition to avoid the potential harm of the waves to people's lives and property.
文摘Geographic visualization is essential for explaining and describing spatiotemporal geographical processes in flow fields.However,due to multi-scale structures and irregular spatial distribution of vortices in complex geographic flow fields,existing two-dimensional visualization methods are susceptible to the effects of data accuracy and sampling resolution,resulting in incomplete and inaccurate vortex information.To address this,we propose an adaptive Line Integral Convolution(LIC)based geographic flow field visualization method by means of rotation distance.Our novel framework of rotation distance and its quantification allows for the effective identification and extraction of vortex features in flow fields effectively.We then improve the LIC algorithm using rotation distance by constructing high-frequency noise from it as input to the convolution,with the integration step size adjusted.This approach allows us to effectively distinguish between vortex and non-vortex fields and adaptively represent the details of vortex features in complex geographic flow fields.Our experimental results show that the proposed method leads to more accurate and effective visualization of the geographic flow fields.
