In recent years,many medical image fusion methods had been exploited to derive useful information from multimodality medical image data,but,not an appropriate fusion algorithm for anatomical and functional medical ***...
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In recent years,many medical image fusion methods had been exploited to derive useful information from multimodality medical image data,but,not an appropriate fusion algorithm for anatomical and functional medical *** this paper,the traditional method of wavelet fusion is improved and a new fusion algorithm of anatomical and functional medical images,in which high-frequency and low-frequency coefficients are studied *** choosing high-frequency coefficients,the global gradient of each sub-image is calculated to realize adaptive fusion,so that the fused image can reserve the functional information;while choosing the low coefficients is based on the analysis of the neighborbood region energy,so that the fused image can reserve the anatomical image's edge and texture *** results and the quality evaluation parameters show that the improved fusion algorithm can enhance the edge and texture feature and retain the function information and anatomical information effectively.
作者:
Liu, QiuxiaHeze Univ
Coll Phys & Elect Engn Heze 274015 Shandong Peoples R China
In order to improve the accuracy and reliability of the collected data, the weighted information fusion algorithm and the Kalman filtering fusion algorithm in multi-sensor data fusion technology are researched and imp...
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In order to improve the accuracy and reliability of the collected data, the weighted information fusion algorithm and the Kalman filtering fusion algorithm in multi-sensor data fusion technology are researched and improved. Firstly, the definition of multi-sensor data fusion and the basic working principle of multi-sensor data fusion are expounded. Structural models of multi-sensor data fusion are introduced, the existing problems of multi-sensor data fusion are analyzed, the development trend of data fusion is pointed out. Secondly, the multi-sensor data fusion algorithms are analyzed, the weighted information fusionfusion algorithm and Kalman filtering algorithm in multi-sensor data fusion technology are focused on. Aiming at the deficiency of the weighted information fusion algorithm, an information fusion algorithm combining the jackknife method and the adaptive weighted method is proposed, and the basic steps of the improved fusion algorithm are given. The algorithm makes full use of the observed values and the estimated values of each historical moment, Quenouille estimation on the estimated values is performed by constructing pseudo-values. On the basis of the traditional Kalman filtering algorithm, an improved filtering algorithm is proposed, and a new state estimation equation is derived, which both treats the field value to prevent the filtering divergence, and introduces the observed value at the next moment to the state estimate at the current moment. Finally, improved fusion algorithms are applied and simulated in intelligent monitoring systems. Application and simulation results show that improved fusion algorithms are effective and superior, they have high reliability and anti-interference performances, the accuracy of the data is greatly increased, and they play a positive role in promoting the wide application of multi-sensor data fusion technology.
To solve the fusion problem of visible and infrared images, based on image fusion algorithm such as region fusion, wavelet transform, spatial frequency, Laplasse Pyramid and principal component analysis, the quality e...
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To solve the fusion problem of visible and infrared images, based on image fusion algorithm such as region fusion, wavelet transform, spatial frequency, Laplasse Pyramid and principal component analysis, the quality evaluation index of image fusion was defined. Then, curve-let transform was used to replace the wavelet change to express the superiority of the curve. It integrated the intensity channel and the infrared image, and then transformed it to the original space to get the fused color image. Finally, two groups of images at different time intervals were used to carry out experiments, and the images obtained after fusion were compared with the images obtained by the first five algorithms, and the quality was evaluated. The experiment showed that the image fusion algorithm based on curve-let transform had good performance, and it can well integrate the information of visible and infrared images. It is concluded that the image fusion algorithm based on curve-let change is a feasible multi-sensor image fusion algorithm based on multi-resolution analysis.
The indoor scene has the characteristics of complexity and Non-Line of Sight (NLOS). Therefore, in the application of cellular network positioning, the layout of the base station has a significant influence on the pos...
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The indoor scene has the characteristics of complexity and Non-Line of Sight (NLOS). Therefore, in the application of cellular network positioning, the layout of the base station has a significant influence on the positioning accuracy. In three-dimensional indoor positioning, the layout of the base station only focuses on the network capacity and the quality of positioning signal. At present, the influence of the coverage and positioning accuracy has not been considered. Therefore, a network element layout optimization algorithm based on improved Adaptive Simulated Annealing and Genetic algorithm (ASA-GA) is proposed in this paper. Firstly, a three-dimensional positioning signal coverage model and a base station layout model are established. Then, the ASA-GA algorithm is proposed for optimizing the base station layout scheme. Experimental results show that the proposed ASA-GA algorithm has a faster convergence speed, which is 16.7% higher than the AG-AC (Adaptive Genetic Combining Ant Colony) algorithm. It takes about 25 generations to achieve full coverage. At the same time, the proposed algorithm has better coverage capability. After optimization of the layout of the network element, the effective coverage rate is increased from 89.77 to 100% and the average location error decreased from 2.874 to 0.983 m, which is about 16% lower than the AG-AC algorithm and 22% lower than the AGA (Adaptive Genetic algorithm) algorithm.
Navigation and positioning system is one of critical subsystems of Synthetic Aperture Sonar (SAS). Based on the Dead Reckoning (DR) navigation and positioning system composed of Fiber-Optic Gyrocompass (IXSEA:OCTANS )...
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Navigation and positioning system is one of critical subsystems of Synthetic Aperture Sonar (SAS). Based on the Dead Reckoning (DR) navigation and positioning system composed of Fiber-Optic Gyrocompass (IXSEA:OCTANS ) and Acoustic Doppler Log (ADL), fusion algorithm which utilize parts of heave compensation outputs of OCTANS and four speed sensor outputs of ADL is provided, available environment of the fusion algorithm is also provided. The simulation results showed that the fusion algorithm is more precise than the common DR algorithm and singer heave compensation outputs from OCTANS.
Target positioning is difficult in indoor environment where Global Positioning System(GPS) always fails to locate for lack of signals. Therefore indoor localization system based on the Wireless Sensor Networks(WSNs) a...
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Target positioning is difficult in indoor environment where Global Positioning System(GPS) always fails to locate for lack of signals. Therefore indoor localization system based on the Wireless Sensor Networks(WSNs) attracted considerable attention due to the growing need for Location Based Service(LBS). Both Ultra-Wideband(UWB) and Bluetooth are widely applied in indoor localization. However, the applicability of them is limited for their high price or poor accuracy. In order to improve the positioning accuracy, stability and cost reduction, a combined indoor localization scheme and a fusion algorithm using characteristics of two positioning methods are proposed. Bayesian Inference and geometry relationships are applied to get the objective function and constrain, and Particle Swarm Optimization(PSO) is employed to obtain the estimated *** results show that the new algorithm can improve the positioning accuracy and reduce the economic price compared with the traditional Least Square(LS) positioning algorithm based on distance.
With ETM+ data(Nantai Island Fuzhou), several fusion algorithms(PCA, MLT, Brovey Transform, HIS) have been applied in image fusion. After image fusion, some criterions(Spectral fidelity, High spatial frequency informa...
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ISBN:
(纸本)9781510830073
With ETM+ data(Nantai Island Fuzhou), several fusion algorithms(PCA, MLT, Brovey Transform, HIS) have been applied in image fusion. After image fusion, some criterions(Spectral fidelity, High spatial frequency information gain, and Classification accuracy, Etc.) have been utilized to evaluate the effect of fusion. Based on the fusion image, unsupervised classification and sequential accuracy assessment have been applied to it. According to the experiment result mentioned above, the paper provides a methodology reference of image fusion to user.
The respiratory rate is a vital parameter that can provide valuable information about the health condition of a patient. The extraction of respiratory information from photoplethysmographic signal (PPG) was actually e...
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ISBN:
(纸本)9781424492695
The respiratory rate is a vital parameter that can provide valuable information about the health condition of a patient. The extraction of respiratory information from photoplethysmographic signal (PPG) was actually encouraged by the reported results, our main goal being to obtain accurate respiratory rate estimation from the PPG signal. We developed a fusion algorithm that identifies the best derived respiratory signals, from which is possible to extract the respiratory rate;based on these, a global respiratory rate is computed using the proposed fusion algorithm. The algorithm is qualitatively tested on real PPG signals recorded by an acquisition system we implemented, using a reflection pulse oximeter sensor. Its performance is also statistically evaluated using benchmark dataset publically available from ***.
Firefly algorithm (FA) is a new meta-heuristic evolutionary algorithm and it has fast calculation and excellent global search capability. Ant Colony algorithm (ACA) has a positive feedback mechanism and distributed op...
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Firefly algorithm (FA) is a new meta-heuristic evolutionary algorithm and it has fast calculation and excellent global search capability. Ant Colony algorithm (ACA) has a positive feedback mechanism and distributed optimization method. Its solution has high accuracy. For characteristics of FA and ACA, the FA and ACA fusion algorithm has advantages of two algorithms to overcome their own disadvantages. In a typical function test, it shows good optimization performance and efficient time performance. And then FA and ACA fusion algorithm is applied to group animation path design to save the animation designer’s labor, and it provides a new design method for the computer animation production.
In this paper, an improved optimal fusion algorithm based on independent fusion of states is proposed for federal filter,which can mainly solve the problem that the state with poor estimation accuracy pollutes other s...
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In this paper, an improved optimal fusion algorithm based on independent fusion of states is proposed for federal filter,which can mainly solve the problem that the state with poor estimation accuracy pollutes other states during fusion, which causes the estimation accuracy of the federated filter system to decrease and the convergence rate to slow down. This improves the stability of the federated filter, thereby improving the robustness of the federal filter. Meanwhile, for the problem of complex fusion weighting matrix, large amount of calculation and poor stability in the fusion algorithm proposed by Carlson, the improved fusion algorithm, the improved fusion algorithm can reduce the complexity of fusion, reduce the operation time of the filtering system, and improve the stability of the filtering system.
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