The detailed kinematic structure of a heavy rain event that occurred in the middle reaches of the Yangtze River was investigated using dual-Doppler radar observation. A variational analysis method was developed to ob... The detailed kinematic structure of a heavy rain event that occurred in the middle reaches of the Yangtze River was investigated using dual-Doppler radar observation. A variational analysis method was developed to obtain the three-dimensional wind fields. Before the analysis, a data preprocessing procedure was carried out, in which the temporal variation with the scanning time interval and the effect of the earth curvature on the data position were taken into account. The analysis shows that a shear line in the lower and middle levels played an important role in the rainfall event. The precipitation fell mainly on the south end of the shear line where southerly flow prevailed and convergence and updraft were obvious. With the movement and decay of the shear line, the precipitation moved and decayed correspondingly.展开更多
Image segmentation is a hot topic in image science. In this paper we present a new variational segmentation model based on the theory of Mumford-Shah model. The aim of our model is to divide noised image, according to...Image segmentation is a hot topic in image science. In this paper we present a new variational segmentation model based on the theory of Mumford-Shah model. The aim of our model is to divide noised image, according to a certain criterion, into homogeneous and smooth regions that should correspond to structural units in the scene or objects of interest. The proposed region-based model uses total variation as a regularization term, and different fidelity term can be used for image segmentation in the cases of physical noise, such as Gaussian, Poisson and multiplicative speckle noise. Our model consists of five weighted terms, two of them are responsible for image denoising based on fidelity term and total variation term, the others assure that the three conditions of adherence to the data, smoothing, and discontinuity detection are met at once. We also develop a primal-dual hybrid gradient algorithm for our model. Numerical results on various synthetic and real images are provided to compare our method with others, these results show that our proposed model and algorithms are effective.展开更多
基金This work was supported by the National Natural Science Foundation of China(Grant No.40175010)
文摘 The detailed kinematic structure of a heavy rain event that occurred in the middle reaches of the Yangtze River was investigated using dual-Doppler radar observation. A variational analysis method was developed to obtain the three-dimensional wind fields. Before the analysis, a data preprocessing procedure was carried out, in which the temporal variation with the scanning time interval and the effect of the earth curvature on the data position were taken into account. The analysis shows that a shear line in the lower and middle levels played an important role in the rainfall event. The precipitation fell mainly on the south end of the shear line where southerly flow prevailed and convergence and updraft were obvious. With the movement and decay of the shear line, the precipitation moved and decayed correspondingly.
基金Supported in part by the NNSF of China(11301129,11271323,91330105,11326033)the Zhejiang Provincial Natural Science Foundation of China(LQ13A010025,LZ13A010002)
文摘Image segmentation is a hot topic in image science. In this paper we present a new variational segmentation model based on the theory of Mumford-Shah model. The aim of our model is to divide noised image, according to a certain criterion, into homogeneous and smooth regions that should correspond to structural units in the scene or objects of interest. The proposed region-based model uses total variation as a regularization term, and different fidelity term can be used for image segmentation in the cases of physical noise, such as Gaussian, Poisson and multiplicative speckle noise. Our model consists of five weighted terms, two of them are responsible for image denoising based on fidelity term and total variation term, the others assure that the three conditions of adherence to the data, smoothing, and discontinuity detection are met at once. We also develop a primal-dual hybrid gradient algorithm for our model. Numerical results on various synthetic and real images are provided to compare our method with others, these results show that our proposed model and algorithms are effective.
