A method based on multi-agents and ANN(Artificial Neural Network)was proposed to solve the pursuit-evasion task in continuous timevarying *** to this method,several autonomous agents with 8 circular sector sensors and...
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A method based on multi-agents and ANN(Artificial Neural Network)was proposed to solve the pursuit-evasion task in continuous timevarying *** to this method,several autonomous agents with 8 circular sector sensors and an ANN controller were used to form a coordinated behavior to capture the *** evolve the controller,NEAT(Neuro Evolution of Augmenting Topologies)and PSO(Particle Swarm Optimization)method were used to optimize the *** simulation experiments show that both methods can successfully evolve the controller to capture the evaders,while NEAT requires less swarm members and consume less time comparing to PSO method.
Transient faults are hard to be detected and located due to their unpredictable nature and short duration, and they are the dominant causations of system failures, which makes it necessary to consider transient fault-...
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An unsupervised change detection method based on spectral clustering and difference image methods for multitemporal single-channel single-polarization synthetic aperture radar (SAR) images is proposed. The difference ...
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An unsupervised change detection method based on spectral clustering and difference image methods for multitemporal single-channel single-polarization synthetic aperture radar (SAR) images is proposed. The difference image is generated by integrating the typical difference image method with Non-Local Filter, which exploits both the spatial neighborhood information and gray similarity information, and can well reduce the speckle noises of SAR images. The spectral clustering algorithm is employed to cluster the difference image into two clusters and get the change map. Compared with traditional clustering algorithms, such as A-means, SC can recognize the clusters of unusual shapes and obtain the globally optimal solutions. Experimental results confirm the effectiveness of the proposed techniques.
In formal language theory of two-dimensions, 2D picture grammars are powerful tools to generate picture languages. In this work, we incorporate the idea of membrane systems (also called P systems) into 2D picture gram...
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In formal language theory of two-dimensions, 2D picture grammars are powerful tools to generate picture languages. In this work, we incorporate the idea of membrane systems (also called P systems) into 2D picture grammars, thus introducing a new kind of picture language generating devices, named P systems with 2D picture grammars. Inspired by the structure and functioning of living cells, such a system has a hierarchical membrane structure, symbol array objects and evolution rules of 2D picture grammars. In each region delimited by the membrane structure, array objects can evolve in a parallel manner according to evolution rules present in the region, like the way biochemical objects evolve in living cells or organisms. The computational result of P system with 2D picture grammars is the set of pictures (rectangular arrays) present in a specific output membrane when the system halts. We obtain several comparison results, which show that with the membrane structure, the generating power of Siromoney matrix grammar, 2D context-free grammar and basic puzzle grammar can be enlarged.
For the special different nature images, we could hardly find particularly desirable approach, and there always exist Gibbs-type artifacts in the results of most methods. A novel Partial Differential Equation (PDE) mo...
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For the special different nature images, we could hardly find particularly desirable approach, and there always exist Gibbs-type artifacts in the results of most methods. A novel Partial Differential Equation (PDE) model is proposed based on image feature for images denoising. The PDE model is adaptive within each region according to the details of the image feature to adjust the size of the diffusion coefficient. So it can be disposed the high gradient noise at the same time better to retain the edge information. We also analyze the performance of the PDE model method. Numerical results show that our algorithm competes favorably with state of the-art TV projection methods to eliminate noise and reduce Gibbs-type artifacts.
In this paper, a novel method for image denoising is proposed which adopts multiscale geometry tool. Firstly the image is decomposed by discrete shearlet transform. The shearlet coefficients of each direction approach...
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In this paper, a novel method for image denoising is proposed which adopts multiscale geometry tool. Firstly the image is decomposed by discrete shearlet transform. The shearlet coefficients of each direction approach the generalized Gaussian distribution. We use the principal component analysis (PCA) for every similarity window of shearlet coefficients. Then we use Generalized Gaussian model of non-local means method to handle the shearlet coefficients. Finally, we reconstruct image with the new shearlet coefficients to obtain the result. Numerical results show that our algorithm competes favorably with nonlocal means algorithms in the case of high noise.
This paper presents a wavelet-based multiscale products scheme for synthetic aperture radar (SAR) image despeckling. A compactly supported quadratic spline function that approximates the first derivative of Gaussian ...
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This paper presents a wavelet-based multiscale products scheme for synthetic aperture radar (SAR) image despeckling. A compactly supported quadratic spline function that approximates the first derivative of Gaussian is employed in the scheme to decompose log-transformed SAR images. The multiplied results of the decomposed coefficients of adjacent scales consist of multiscale products. The multiscale products can sharp the important structures while weakening noise. A spatially selective neighborhood technique by iteratively selecting neighborhood system in the multiscale products is introduced in searching the important structure information. The influence of the spatial information is imposed on the multiscale products, instead of on the wavelet coefficients, which improves the capability of identifying important features. Experiments show that the proposed scheme is better in SAR image despeckling and preserving edges and detail information than other waveletbased multiscale products methods.
In this paper, we focus on the distribution of eigenvalues, and based on Gaussian assumption, then we do an analysis of the eigenvalues potential for POL-SAR classification. Generally, we use Gaussian mixture model to...
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In this paper, we focus on the distribution of eigenvalues, and based on Gaussian assumption, then we do an analysis of the eigenvalues potential for POL-SAR classification. Generally, we use Gaussian mixture model to describe the distribution of the eigenvalue and Bayesian classifier to achieve the POL-SAR pixel classification. The method is tested with the NASA/JPL AIRSAR data.
This paper proposes a improved non-local means (NLM) filter for image denoising. Due to the drawback that the similarity is computed based on the noisy image, the traditional NLM method easily generates the artifacts ...
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This paper proposes a improved non-local means (NLM) filter for image denoising. Due to the drawback that the similarity is computed based on the noisy image, the traditional NLM method easily generates the artifacts in case of high-level noise. The proposed method first preprocesses the noisy image by Gaussian filter. Then, a moving window at each pixel of the noisy image is chosen as the search window, and meanwhile, a improved calculation method of spatial distance based on the preprocessed image is used for computing the similarity. Finally, combining the improved distance with search window based on the noisy image, the intensity of each pixel is restored as the traditional NLM method. The standard images are used to evaluate restoration performance of the proposed method. Additionally, the application on medical image denoising also demonstrates that our method is practical.
A low-cost device using acoustic method for measuring open-end tube length is developed. The proposed device is aimed to get the length of the tubes which are piled up together, and only one end of which is available ...
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A low-cost device using acoustic method for measuring open-end tube length is developed. The proposed device is aimed to get the length of the tubes which are piled up together, and only one end of which is available in the warehouse or dumping areas. The device contains the emitting and receiving probes to echo the sound pulse and receive the reflection sound wave, and has been developed with discrete component circuits whose key part is the logical control circuit based on ARM. Experiments are performed in the open tubes with the lengths between 0.85 m to 6 m. The measurement error is below 0.5 cm. For the tubes blocked by the cement or earth, the device can detect the location of obstruction automatically. Based on the acoustic method, experiments are also conducted in the blocked tubes based on Matlab software, and the analysis of the reflection wave is given.
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