Typhoon Center Location Based On Embedded Hidden Markov Model And Cross-Entropy

Typhoon is one of the most deadly weathers. It is significant to locate the position of typhoon center. This work is still on the study stage. One of the methods is based on shape, which is difficult to adapt to all conditions due to typhoon's complex motion and deformable shapes. Another method is to analyze rotation feature, which deviates from the truth because typhoon is seemed as rigid body.No matter how typhoon changes in the course of moving, energy is least in the typhoon center. Based on this general feature, a new method is presented in this paper, which is by cross-entropy and embedded hidden Markov model based onwavelet-domain. It is done by five steps as follows:1. Extract the dynamic information from the differential image.2. Get wavelet coefficients of differential images. The analysis is based on wavelet coefficient, which can reduce the dimension of observation vector's space.3. Analyze the space correlation in the single differential image: sample the wavelet coefficients with window and segment the image into the equal blocks. Train and recognize the sampled wavelet coefficients by embedded hidden Markov model. Segment the differential image into blocks over again by embedded Viterbi and K-means algorithm according to the space correlation.4. Analyze the time correlation in the differential image sequences: Use cross-entropy to track the blocks of image sequences according to the time correlation along the time axes. Compared to the old methods based on single image, the method which is based on many images can extend the used information. Moreover, it can improve the precision by analyzing the space and time correlation.5. Measure the motion energy of the blocks with the energy function and locate the position of typhoon center.This method has succeeded in extending the scope of the applied object.