In this paper, radial basis functions are used to obtain the solution of evolution equations which appear in variational level set method based image segmentation. In this method, radial basis functions are used to in...In this paper, radial basis functions are used to obtain the solution of evolution equations which appear in variational level set method based image segmentation. In this method, radial basis functions are used to interpolate the implicit level set function of the evolution equation with a high level of accuracy and smoothness. Then, the original initial value problem is discretized into an interpolation problem. Accordingly, the evolution equation is converted into a set of coupled ordinary differential equations, and a smooth evolution can be retained. Compared with finite difference scheme based level set approaches, the complex and costly re-initialization procedure is unnecessary. Numerical examples are also given to show the efficiency of the method.展开更多
Selective logging is well-recognized as an effective practice in sustainable forest management.However,the ecological efficiency or resilience of the residual stand is often in doubt.Recovery time depends on operation...Selective logging is well-recognized as an effective practice in sustainable forest management.However,the ecological efficiency or resilience of the residual stand is often in doubt.Recovery time depends on operational variables,diversity,and forest structure.Selective logging is excellent but is open to changes.This may be resolved by mathematical programming and this study integrates the economic-ecological aspects in multi-objective function by applying two evolutionary algorithms.The function maximizes remaining stand diversity,merchantable logs,and the inverse of distance between trees for harvesting and log landings points.The Brazilian rainforest database(566 trees)was used to simulate our 216-ha model.The log landing design has a maximum volume limit of 500 m3.The nondominated sorting genetic algorithm was applied to solve the main optimization problem.In parallel,a sub-problem(p-facility allocation)was solved for landing allocation by a genetic algorithm.Pareto frontier analysis was applied to distinguish the gradientsα-economic,β-ecological,andγ-equilibrium.As expected,the solutions have high diameter changes in the residual stand(average removal of approximately 16 m^(3) ha^(-1)).All solutions showed a grouping of trees selected for harvesting,although there was no formation of large clearings(percentage of canopy removal<7%,with an average of 2.5 ind ha^(-1)).There were no differences in floristic composition by preferentially selecting species with greater frequency in the initial stand for harvesting.This implies a lower impact on the demographic rates of the remaining stand.The methodology should support projects of reduced impact logging by using spatial-diversity information to guide better practices in tropical forests.展开更多
Image segmentation is one of important steps on pattern recognition study in the course of wood across-compression. By comparing and studying processing methods in finding cell space and cell wall, this paper puts for...Image segmentation is one of important steps on pattern recognition study in the course of wood across-compression. By comparing and studying processing methods in finding cell space and cell wall, this paper puts forward some image segmentation methods that are suitable for study of cell images of wood crossgrained compression. The method of spline function fitting was used for linking edges of cell, which perfects the study of pattern recognition in the course of wood across-compression.展开更多
Photoacoustic imaging has many advantages in ophthalmic application including high-resolution,requirement of no exogenous contrast agent,and noninvasive acquisition of both morphologic and functional information.Howev...Photoacoustic imaging has many advantages in ophthalmic application including high-resolution,requirement of no exogenous contrast agent,and noninvasive acquisition of both morphologic and functional information.However,due to the limited depth of focus of the imaging method and large curvature of the eye,it remains a challenge to obtain high quality vascular image of entire anterior segment.Here,we proposed a new method to achieve high quality imaging of anterior segment.The new method applied a curvature imaging strategy based on only one time scanning,and hence is time efficient and more suitable for ophthalmic imaging compared to previously reported methods using similar strategy.A custom-built photoacoustic imaging system was adapted for ophthalmic application and a customized image processing method was developed to quantitatively analyze both morphologic and functional information in vasculature of the anterior segment.The results showed that the new method improved the image quality of anterior segment significantly compared to that of conventional high resolution photoacoustic imaging.More importantly,we applied the new method to study ophthalmic disease in an in vivo mouse model for the first time.The results verified the suitability and advantages of the new method for imaging the entire anterior segment and the numerous potentials of applying it in ophthalmic imaging in future.展开更多
Aiming to deal with the difficult issues of terrain data model simplification and crack disposal,the paper proposed an improved level of detail(LOD)terrain rendering algorithm,in which a variation coefficient of eleva...Aiming to deal with the difficult issues of terrain data model simplification and crack disposal,the paper proposed an improved level of detail(LOD)terrain rendering algorithm,in which a variation coefficient of elevation is introduced to express the undulation of topography.Then the coefficient is used to construct a node evaluation function in the terrain data model simplification step.Furthermore,an edge reduction strategy is combined with the improved restrictive quadtree segmentation to handle the crack problem.The experiment results demonstrated that the proposed method can reduce the amount of rendering triangles and enhance the rendering speed on the premise of ensuring the rendering effect compared with a traditional LOD algorithm.展开更多
The S/N of an underwater image is low and has a fuzzy edge.If using traditional methods to process it directly,the result is not satisfying.Though the traditional fuzzy C-means algorithm can sometimes divide the image...The S/N of an underwater image is low and has a fuzzy edge.If using traditional methods to process it directly,the result is not satisfying.Though the traditional fuzzy C-means algorithm can sometimes divide the image into object and background,its time-consuming computation is often an obstacle.The mission of the vision system of an autonomous underwater vehicle (AUV) is to rapidly and exactly deal with the information about the object in a complex environment for the AUV to use the obtained result to execute the next task.So,by using the statistical characteristics of the gray image histogram,a fast and effective fuzzy C-means underwater image segmentation algorithm was presented.With the weighted histogram modifying the fuzzy membership,the above algorithm can not only cut down on a large amount of data processing and storage during the computation process compared with the traditional algorithm,so as to speed up the efficiency of the segmentation,but also improve the quality of underwater image segmentation.Finally,particle swarm optimization (PSO) described by the sine function was introduced to the algorithm mentioned above.It made up for the shortcomings that the FCM algorithm can not get the global optimal solution.Thus,on the one hand,it considers the global impact and achieves the local optimal solution,and on the other hand,further greatly increases the computing speed.Experimental results indicate that the novel algorithm can reach a better segmentation quality and the processing time of each image is reduced.They enhance efficiency and satisfy the requirements of a highly effective,real-time AUV.展开更多
A novel active contour model is proposed, which incorporates local information distributions in a fuzzy energy function to effectively deal with the intensity inhomogeneity. Moreover, the proposed model is convex with...A novel active contour model is proposed, which incorporates local information distributions in a fuzzy energy function to effectively deal with the intensity inhomogeneity. Moreover, the proposed model is convex with respect to the variable which is used for extracting the contour. This makes the model independent on the initial condition and suitable for an automatic segmentation. Furthermore, the energy function is minimized in a computationally efficient way by calculating the fuzzy energy alterations directly. Experiments are carried out to prove the performance of the proposed model over some existing methods. The obtained results confirm the efficiency of the method.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant No.11101454)the Educational Commission Foundation of Chongqing City,China (Grant No.KJ130626)the Program of Innovation Team Project in University of Chongqing City,China (Grant No.KJTD201308)
文摘In this paper, radial basis functions are used to obtain the solution of evolution equations which appear in variational level set method based image segmentation. In this method, radial basis functions are used to interpolate the implicit level set function of the evolution equation with a high level of accuracy and smoothness. Then, the original initial value problem is discretized into an interpolation problem. Accordingly, the evolution equation is converted into a set of coupled ordinary differential equations, and a smooth evolution can be retained. Compared with finite difference scheme based level set approaches, the complex and costly re-initialization procedure is unnecessary. Numerical examples are also given to show the efficiency of the method.
基金supported by the Coordenacao de Aperfeicoamento de Pessoal de Nível Superior–Brasil (CAPES)–Finance Code 001the Postgraduate Programme in Forest Engineering of the Federal University of Lavras (PPGEF/UFLA)and Group of Optimization and Planning (GOPLAN/UFLA/LEMAF-Forest Management Research Lab)。
文摘Selective logging is well-recognized as an effective practice in sustainable forest management.However,the ecological efficiency or resilience of the residual stand is often in doubt.Recovery time depends on operational variables,diversity,and forest structure.Selective logging is excellent but is open to changes.This may be resolved by mathematical programming and this study integrates the economic-ecological aspects in multi-objective function by applying two evolutionary algorithms.The function maximizes remaining stand diversity,merchantable logs,and the inverse of distance between trees for harvesting and log landings points.The Brazilian rainforest database(566 trees)was used to simulate our 216-ha model.The log landing design has a maximum volume limit of 500 m3.The nondominated sorting genetic algorithm was applied to solve the main optimization problem.In parallel,a sub-problem(p-facility allocation)was solved for landing allocation by a genetic algorithm.Pareto frontier analysis was applied to distinguish the gradientsα-economic,β-ecological,andγ-equilibrium.As expected,the solutions have high diameter changes in the residual stand(average removal of approximately 16 m^(3) ha^(-1)).All solutions showed a grouping of trees selected for harvesting,although there was no formation of large clearings(percentage of canopy removal<7%,with an average of 2.5 ind ha^(-1)).There were no differences in floristic composition by preferentially selecting species with greater frequency in the initial stand for harvesting.This implies a lower impact on the demographic rates of the remaining stand.The methodology should support projects of reduced impact logging by using spatial-diversity information to guide better practices in tropical forests.
文摘Image segmentation is one of important steps on pattern recognition study in the course of wood across-compression. By comparing and studying processing methods in finding cell space and cell wall, this paper puts forward some image segmentation methods that are suitable for study of cell images of wood crossgrained compression. The method of spline function fitting was used for linking edges of cell, which perfects the study of pattern recognition in the course of wood across-compression.
基金financial supports from the National Natural Science Foundation of China(NSFC)(Grants No.91739117,31570952,81873919,81371662 and 81927807)Shenzhen Science and Technology Innovation(Grant No.JCYJ20170413153129570)+1 种基金Beijing Natural Science Foundation of China(Grant No.3122010)。
文摘Photoacoustic imaging has many advantages in ophthalmic application including high-resolution,requirement of no exogenous contrast agent,and noninvasive acquisition of both morphologic and functional information.However,due to the limited depth of focus of the imaging method and large curvature of the eye,it remains a challenge to obtain high quality vascular image of entire anterior segment.Here,we proposed a new method to achieve high quality imaging of anterior segment.The new method applied a curvature imaging strategy based on only one time scanning,and hence is time efficient and more suitable for ophthalmic imaging compared to previously reported methods using similar strategy.A custom-built photoacoustic imaging system was adapted for ophthalmic application and a customized image processing method was developed to quantitatively analyze both morphologic and functional information in vasculature of the anterior segment.The results showed that the new method improved the image quality of anterior segment significantly compared to that of conventional high resolution photoacoustic imaging.More importantly,we applied the new method to study ophthalmic disease in an in vivo mouse model for the first time.The results verified the suitability and advantages of the new method for imaging the entire anterior segment and the numerous potentials of applying it in ophthalmic imaging in future.
基金Supported by the National Natural Science Foundation of China(61363075)the National High Technology Research and Development Program of China(863 Program)(2012AA12A308)the Yue Qi Young Scholars Program of China University of Mining&Technology,Beijing(800015Z1117)
文摘Aiming to deal with the difficult issues of terrain data model simplification and crack disposal,the paper proposed an improved level of detail(LOD)terrain rendering algorithm,in which a variation coefficient of elevation is introduced to express the undulation of topography.Then the coefficient is used to construct a node evaluation function in the terrain data model simplification step.Furthermore,an edge reduction strategy is combined with the improved restrictive quadtree segmentation to handle the crack problem.The experiment results demonstrated that the proposed method can reduce the amount of rendering triangles and enhance the rendering speed on the premise of ensuring the rendering effect compared with a traditional LOD algorithm.
基金Supported by the National Natural Science Foundation of China under Grant No.50909025/E091002the Open Research Foundation of SKLab AUV, HEU under Grant No.2008003
文摘The S/N of an underwater image is low and has a fuzzy edge.If using traditional methods to process it directly,the result is not satisfying.Though the traditional fuzzy C-means algorithm can sometimes divide the image into object and background,its time-consuming computation is often an obstacle.The mission of the vision system of an autonomous underwater vehicle (AUV) is to rapidly and exactly deal with the information about the object in a complex environment for the AUV to use the obtained result to execute the next task.So,by using the statistical characteristics of the gray image histogram,a fast and effective fuzzy C-means underwater image segmentation algorithm was presented.With the weighted histogram modifying the fuzzy membership,the above algorithm can not only cut down on a large amount of data processing and storage during the computation process compared with the traditional algorithm,so as to speed up the efficiency of the segmentation,but also improve the quality of underwater image segmentation.Finally,particle swarm optimization (PSO) described by the sine function was introduced to the algorithm mentioned above.It made up for the shortcomings that the FCM algorithm can not get the global optimal solution.Thus,on the one hand,it considers the global impact and achieves the local optimal solution,and on the other hand,further greatly increases the computing speed.Experimental results indicate that the novel algorithm can reach a better segmentation quality and the processing time of each image is reduced.They enhance efficiency and satisfy the requirements of a highly effective,real-time AUV.
文摘A novel active contour model is proposed, which incorporates local information distributions in a fuzzy energy function to effectively deal with the intensity inhomogeneity. Moreover, the proposed model is convex with respect to the variable which is used for extracting the contour. This makes the model independent on the initial condition and suitable for an automatic segmentation. Furthermore, the energy function is minimized in a computationally efficient way by calculating the fuzzy energy alterations directly. Experiments are carried out to prove the performance of the proposed model over some existing methods. The obtained results confirm the efficiency of the method.
