Aero-optic effects cause distortions, including blurring, vibration, deformation and spatial shifting, of the objects in the image obtained by the infra-red sensor. Contributions of this paper are in the following two...
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ISBN:
(纸本)9781424439027
Aero-optic effects cause distortions, including blurring, vibration, deformation and spatial shifting, of the objects in the image obtained by the infra-red sensor. Contributions of this paper are in the following two aspects. First, the correctness of the theoretical point spread function (PSF) representing the aero-optic effects, which had been derived in our previous research, is validated experimentally. Second, in order to restore the aero-optically degraded images, an improved Landweber iteration method is proposed, where, instead of being fixed, the relaxation factor is updated adaptively at each iteration. Experiments have been carried out and results demonstrate that the proposed method introduces improved restoration results with better convergence.
Several neutrosophic combination rules based on the Dempster-Shafer theory (DST) and Dezert-Smarandache theory (DSmT) are presented in this study. The new information fusing approaches proposed the neutrosophic belief...
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In this paper, we presented a ringing metric to evaluate the quality of images restored using iterative image restoration algorithms. A ringing metrics is used to assessment the restored images based on the Gabor filt...
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In this paper, we presented a ringing metric to evaluate the quality of images restored using iterative image restoration algorithms. A ringing metrics is used to assessment the restored images based on the Gabor filter. The experimental results validate the proposed method perform well over a wide range of restoration image ringing levels assessment. And the proposed model has given good agreement with observer ratings obtained in subjective experiments.
Multi-robot tracking of mobile target is studied in the paper, which is based on the communication and sensors. For an independent tracking robot, the processes are separated into three layers and four tasks, and allo...
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Multi-robot tracking of mobile target is studied in the paper, which is based on the communication and sensors. For an independent tracking robot, the processes are separated into three layers and four tasks, and allocated to different robots for distinct roles in tracking, which is named the Distributed Decision control System (DDCS). After that, two tracking models, centralized and distributed models, are designed for multi-robot tracking. Furthermore, a Proportional Navigation Guidance Law (PNGL) and l-ϕ formation control algorithm are mentioned to realize the robot motion control. At last the simulation has shown the feasibility and validity of both models.
Combining bottom-up and top-down attention influences, a novel region extraction model which based on object-accumulated visual attention mechanism is proposed in this paper. Compared with early research, the new appr...
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Combining bottom-up and top-down attention influences, a novel region extraction model which based on object-accumulated visual attention mechanism is proposed in this paper. Compared with early research, the new approach brings in prior information at the proper time, updates scan path dynamically, needs less computational resources and reduces the probability to direct the attention to a less-meaning area. The application to search an airport target in remote sensing image was provided, through which the novel mechanism that how visual attention chose the area was described. Compared with another two region extraction models, experimental results confirm the effectiveness of the approach proposed in this paper.
To infrared images, the contrast of target and background is low, dim small targets have no concrete shapes and their textures cannot be reliable predicted. The paper puts forward a novel algorithm to fuse mid-wave an...
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To infrared images, the contrast of target and background is low, dim small targets have no concrete shapes and their textures cannot be reliable predicted. The paper puts forward a novel algorithm to fuse mid-wave and long-wave infrared images and detect targets. Firstly, the source images are decomposed by wavelet transformation. In usual, targets in infrared images are man-made, and their fractal dimension is different comparing with natural background. In wavelet transformation domain high-frequency part, we calculate local fractal dimension and set up fusion rule to merge corresponding sub-images of two matching source images. In low-frequency, we extract local maximum gray level to fuse them. Then reconstruct image by wavelet inverse transformation and obtain fused result image. In fusion results, the contrast between targets and background has obvious changes. And targets can be detected using contrast threshold. The experimental results show that the method proposed in this paper using wavelet transformation fractal dimension to fuse dual band infrared images, and then detect targets is better than using mid-wave or long -wave infrared images detect targets alone.
A quick 3D needle segmentation algorithm for 3D US data is described in this paper. The algorithm includes the 3D quick randomized Hough transform (3DGHT), which is based on the 3D randomized Hough transform and coars...
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A quick 3D needle segmentation algorithm for 3D US data is described in this paper. The algorithm includes the 3D quick randomized Hough transform (3DGHT), which is based on the 3D randomized Hough transform and coarse-fine searching strategy. We tested it with water phantom. The results show that our algorithm works well in 3D US images with angular deviation less than 1 degree and position deviation less than 1 mm, and the computational time of segmentation with 35 MB data is within 1s.
This paper describes a novel 3D needle segmentation algorithm for 3DUS data. The algorithm includes the 3D Gray-level Hough Transform (3DGHT), which is based on the representation (ψ, θ, ρ, α) of straight lines in...
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Most experimental and decoding algorithm studies of brain neural signals assume that neurons transmit information as a rate coding, but recent studies on the fast cortical computations indicate that temporal coding is...
Most experimental and decoding algorithm studies of brain neural signals assume that neurons transmit information as a rate coding, but recent studies on the fast cortical computations indicate that temporal coding is probably a more biologically plausible scheme used by neurons. We introduce spiking neural networks (SNN) which consist of spiking neurons propagate information by the timing of spikes to analyze the cortical neural spike trains directly without temporal information lost. The SNN based temporal pattern classification is compared with the conventional artificial neural networks (ANN) based firing rate analysis. The results show that the SNN algorithm can achieve higher accuracy, which demonstrates that temporal coding is a viable code for fast neural information processing and the SNN approach is suitable for recognizing the temporal pattern in the cortical neural signals.
A fuzzy logic controller (FLC) is designed to achieve course-keeping for mooring shifting system, which is the main system of non self-propelled vessels. Compared with manual operation, the automatic operation and mon...
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A fuzzy logic controller (FLC) is designed to achieve course-keeping for mooring shifting system, which is the main system of non self-propelled vessels. Compared with manual operation, the automatic operation and monitoring system with the FLC can perform higher precision and efficiency. The particle swarm optimization (PSO) algorithm is introduced to optimize the proposed FLCpsilas parameters. A series of simulation studies have been undertaken to compare the performance of a basis FLC and PSO based FLC. The results demonstrate that the latter has the better controlling quality.
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