To preserve the original signal as much as possible and filter random noises as many as possible in image processing,a threshold optimization-based adaptive template filtering algorithm was proposed.Unlike conventiona...To preserve the original signal as much as possible and filter random noises as many as possible in image processing,a threshold optimization-based adaptive template filtering algorithm was proposed.Unlike conventional filters whose template shapes and coefficients were fixed,multi-templates were defined and the right template for each pixel could be matched adaptively based on local image characteristics in the proposed method.The superiority of this method was verified by former results concerning the matching experiment of actual image with the comparison of conventional filtering methods.The adaptive search ability of immune genetic algorithm with the elitist selection and elitist crossover(IGAE) was used to optimize threshold t of the transformation function,and then combined with wavelet transformation to estimate noise variance.Multi-experiments were performed to test the validity of IGAE.The results show that the filtered result of t obtained by IGAE is superior to that of t obtained by other methods,IGAE has a faster convergence speed and a higher computational efficiency compared with the canonical genetic algorithm with the elitism and the immune algorithm with the information entropy and elitism by multi-experiments.展开更多
The authors propose a numerical algorithm for the two-dimensional Navier-Stokes equations written in stream function-vorticity formulation. The total time derivative term is treated with a first order characteristics ...The authors propose a numerical algorithm for the two-dimensional Navier-Stokes equations written in stream function-vorticity formulation. The total time derivative term is treated with a first order characteristics method. The space approximation is based on a piecewise continuous finite element method. The proposed algorithm is used to simulate the mechanical aeration process in lakes. Such process is used to combat the degradation of the water quality due to the eutrophication phenomena. For this application high computing facilities and capacities are required. In order to optimize the computing time and make possible the simulation of real applications, the authors propose a parallel implementation of the numerical algorithm. The parallelization technique is performed using the Message Passing Interface. The efficiency of the proposed numerical algorithm is illustrated by some numerical results.展开更多
基金Project(20040533035) supported by the National Research Foundation for the Doctoral Program of Higher Education of ChinaProject (60874070) supported by the National Natural Science Foundation of China
文摘To preserve the original signal as much as possible and filter random noises as many as possible in image processing,a threshold optimization-based adaptive template filtering algorithm was proposed.Unlike conventional filters whose template shapes and coefficients were fixed,multi-templates were defined and the right template for each pixel could be matched adaptively based on local image characteristics in the proposed method.The superiority of this method was verified by former results concerning the matching experiment of actual image with the comparison of conventional filtering methods.The adaptive search ability of immune genetic algorithm with the elitist selection and elitist crossover(IGAE) was used to optimize threshold t of the transformation function,and then combined with wavelet transformation to estimate noise variance.Multi-experiments were performed to test the validity of IGAE.The results show that the filtered result of t obtained by IGAE is superior to that of t obtained by other methods,IGAE has a faster convergence speed and a higher computational efficiency compared with the canonical genetic algorithm with the elitism and the immune algorithm with the information entropy and elitism by multi-experiments.
文摘The authors propose a numerical algorithm for the two-dimensional Navier-Stokes equations written in stream function-vorticity formulation. The total time derivative term is treated with a first order characteristics method. The space approximation is based on a piecewise continuous finite element method. The proposed algorithm is used to simulate the mechanical aeration process in lakes. Such process is used to combat the degradation of the water quality due to the eutrophication phenomena. For this application high computing facilities and capacities are required. In order to optimize the computing time and make possible the simulation of real applications, the authors propose a parallel implementation of the numerical algorithm. The parallelization technique is performed using the Message Passing Interface. The efficiency of the proposed numerical algorithm is illustrated by some numerical results.
