Ray casting algorithm can obtain a better quality image in volume rendering, however, it exists some problems, such as powerful computing capacity and slow rendering speed. How to improve the re-sampled speed is a key...Ray casting algorithm can obtain a better quality image in volume rendering, however, it exists some problems, such as powerful computing capacity and slow rendering speed. How to improve the re-sampled speed is a key to speed up the ray casting algorithm. An algorithm is introduced to reduce matrix computation by matrix transformation characteristics of re-sampling points in a two coordinate system. The projection of 3-D datasets on image plane is adopted to reduce the number of rays. Utilizing boundary box technique avoids the sampling in empty voxel. By extending the Bresenham algorithm to three dimensions, each re-sampling point is calculated. Experimental results show that a two to three-fold improvement in rendering speed using the optimized algorithm, and the similar image quality to traditional algorithm can be achieved. The optimized algorithm can produce the required quality images, thus reducing the total operations and speeding up the volume rendering.展开更多
From the controlling equations of atmosphere motion, Prandtl's mixing length theory is used to derive the atmospheric turbulence models, such as Burgers equation model and Burgers-KdV equation model. And then the ...From the controlling equations of atmosphere motion, Prandtl's mixing length theory is used to derive the atmospheric turbulence models, such as Burgers equation model and Burgers-KdV equation model. And then the projective Riccati equations are applied to solve these atmospheric turbulence models, where much more patterns are obtained, including solitary wave pattern, singular pattern, and so on.展开更多
To solve the problems associated with low resolution and high computational effort infinite time,this paper proposes a fast forward modeling method for muon energy loss transmission tomography based on a model voxeliza...To solve the problems associated with low resolution and high computational effort infinite time,this paper proposes a fast forward modeling method for muon energy loss transmission tomography based on a model voxelization energy loss projection algorithm.First,the energy loss equation for muon transmission tomography is derived from the Bethe–Bloch formula,and the imaging region is then dissected into several units using the model voxelization method.Thereafter,the three-dimensional(3-D)imaging model is discretized into parallel and equally spaced two-dimensional(2-D)slices using the model layering method to realize a dimensional reduction of the 3-D volume data and accelerate the forward calculation speed.Subsequently,the muon energy loss transmission tomography equation is discretized using the ray energy loss projection method to establish a set of energy loss equations for the muon penetration voxel model.Finally,the muon energy loss values at the outgoing point are obtained by solving the projection coefficient matrix of the ray length-weighted model,achieving a significant reduction in the number of muons and improving the computational efficiency.A comparison of our results with the simulation results based on the Monte Carlo method verifies the accuracy and effectiveness of the algorithm proposed in this paper.The metallic mineral identification tests show that the proposed algorithm can quickly identify high-density metallic minerals.The muon energy loss response can accurately identify the boundary of the anomalies and their spatial distribution characteristics.展开更多
文摘Ray casting algorithm can obtain a better quality image in volume rendering, however, it exists some problems, such as powerful computing capacity and slow rendering speed. How to improve the re-sampled speed is a key to speed up the ray casting algorithm. An algorithm is introduced to reduce matrix computation by matrix transformation characteristics of re-sampling points in a two coordinate system. The projection of 3-D datasets on image plane is adopted to reduce the number of rays. Utilizing boundary box technique avoids the sampling in empty voxel. By extending the Bresenham algorithm to three dimensions, each re-sampling point is calculated. Experimental results show that a two to three-fold improvement in rendering speed using the optimized algorithm, and the similar image quality to traditional algorithm can be achieved. The optimized algorithm can produce the required quality images, thus reducing the total operations and speeding up the volume rendering.
文摘From the controlling equations of atmosphere motion, Prandtl's mixing length theory is used to derive the atmospheric turbulence models, such as Burgers equation model and Burgers-KdV equation model. And then the projective Riccati equations are applied to solve these atmospheric turbulence models, where much more patterns are obtained, including solitary wave pattern, singular pattern, and so on.
基金supported by the National Key Research and Development Project of China (2016YFC0303104)the National Natural Science Foundation of China(41304090)。
文摘To solve the problems associated with low resolution and high computational effort infinite time,this paper proposes a fast forward modeling method for muon energy loss transmission tomography based on a model voxelization energy loss projection algorithm.First,the energy loss equation for muon transmission tomography is derived from the Bethe–Bloch formula,and the imaging region is then dissected into several units using the model voxelization method.Thereafter,the three-dimensional(3-D)imaging model is discretized into parallel and equally spaced two-dimensional(2-D)slices using the model layering method to realize a dimensional reduction of the 3-D volume data and accelerate the forward calculation speed.Subsequently,the muon energy loss transmission tomography equation is discretized using the ray energy loss projection method to establish a set of energy loss equations for the muon penetration voxel model.Finally,the muon energy loss values at the outgoing point are obtained by solving the projection coefficient matrix of the ray length-weighted model,achieving a significant reduction in the number of muons and improving the computational efficiency.A comparison of our results with the simulation results based on the Monte Carlo method verifies the accuracy and effectiveness of the algorithm proposed in this paper.The metallic mineral identification tests show that the proposed algorithm can quickly identify high-density metallic minerals.The muon energy loss response can accurately identify the boundary of the anomalies and their spatial distribution characteristics.
