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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Yang, Xin Ding, Mingyue Zhou, Chengping Cai, Chao Yu, Qi Shao, Shuai Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

This paper presented improved Sparse A-Star Search (SAS) algorithm to pursue a fast route planner for Unmanned Aerial Vehicles (UAVs) on-ship applications. Our approach can quickly produce 3-D trajectories composed by a set of successive navigation points from certain known initial locations to predetermined target locations. The result routes are not only ensuring collision avoidance with the environmental obstacles, but also satisfying specific routes constraints and objectives. The experiment results demonstrated the feasibility of the method, which makes our route planner be more useful in real systems. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Ships

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Path planning for UAV based on quantum-behaved particle swarm optimization

Path planning for UAV based on quantum-behaved particle swar...

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Fu, Yangguang Ding, Mingyue Zhou, Chengping Cai, Chao Sun, Yangguang Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

Based on quantum-behaved particle swarm optimization (QPSO), a novel path planner for unmanned aerial vehicle (UAV) is employed to generate a safe and flyable path. The standard particle swarm optimization (PSO) and quantum-behaved particle swarm optimization (QPSO) are presented and compared through a UAV path planning application. Every particle in swarm represents a potential path in search space. For the purpose of pruning the search space, constraints are incorporated into the pre-specified cost function, which is used to evaluate whether a particle is good or not. As the system iterated, each particle is pulled toward its local attractor, which is located between the personal best position (pbest) and the global best position (gbest) based on the interaction of particles' individual searches and group's public search. For the sake of simplicity, we only consider planning the projection of path on the plane and assume threats are static instead of moving. Simulation results demonstrated the effectiveness and feasibility of the proposed approach. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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Gravity gradient-terrain aided navigation based on particle filter

Gravity gradient-terrain aided navigation based on particle ...

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MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Xiong, Ling Ma, Jie Tian, Jin-Wen State Key Lab. for Multi-spectral Information Processing Technologies Key Lab. of Education Ministry for Image Processing and Intelligence Control Huazhong University of Science and Technology Wuhan 430074 China College of Information Science and Engineering Wuhan University of Science and Technology Wuhan 430081 China

ISBN: (纸本)9780819478092

Based on Particle Filter, Gravity Gradient-Terrain aided position technology is proposed in this paper. With the sensitivity of gravity gradient to terrain, the gravity gradient reference map can be computed from the local terrain elevation data. The position can be actualized through matching the real-time measured gravity gradient data to the prepared gravity gradient reference map. The most widely used approximate filtering method is the extended Kaman filter (EKF). EKF is computationally simple but, the convergence of the state estimation for the position is not guaranteed. Particle filter (PF) makes use of the non-linear state and measurement functions, no linearization technology is needed. PF can assure the convergence of the state estimation which follows from the classical results on convergence of Bayesian estimators. Simulations have been done and Particle filter has been shown to be a superior alternative to the EKF in the gravity gradient-terrain matching navigation systems. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Extended Kalman filters

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High-Precision Discrete Convolution Algorithm Based on Moments

High-Precision Discrete Convolution Algorithm Based on Momen...

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WRI International Conference on Communications and Mobile Computing, CMC

作者： Jianguo Liu Zhenbing Liu Guoyou Wang Key Laboratory of Education Ministry for Image Processing and Intelligent Control State Key Laboratory of Multispectral Information Processing Technologies Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

Convolution is an important and useful operation in the fields of digital signal processing. In this paper, based on the previous work of performing discrete Fourier transform (DFT) via linear sums of discrete moments, we have made development to eliminate multiplications in discrete Fourier transforms by performing appropriate bit operations and shift operations in binary system, which can be implemented by integer additions of fixed points; then using the convolution theorem with the DFT, we compute the convolution with two DFTs, a point-by-point product, and an inverse DFT. Our algorithm involves fewer multiplications and can deal with arbitrary length signals.

关键词： Convolution Signal processing algorithms Discrete Fourier transforms Very large scale integration Algorithm design and analysis Laboratories educational technology Digital signal processing Mobile communication Mobile computing

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High-Precision and Arbitrary-length Fixed-Point Fast Hartley Transform without Multiplications

High-Precision and Arbitrary-length Fixed-Point Fast Hartley...

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WRI International Conference on Communications and Mobile Computing, CMC

作者： Zhenbing Liu Jianguo Liu Guoyou Wang Key Laboratory of Education Ministry for Image Processing and Intelligent Control State Key Laboratory of Multispectral Information Processing Technologies Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

Discrete Hartley transform (DHT) is an important tool in digital signal processing. In this paper, based on our previous work of performing DHT via linear sums of discrete moments, we have made development to eliminate multiplications in discrete Hartley transforms by performing appropriate bit operations and shift in binary system, which can be implemented by integer additions of fixed points. An efficient and regular systolic array is designed to implement it, and the complexity analysis is also given. Different to other fast Hartley transforms, our algorithm can deal with arbitrary length signals and get high precision. The approach is also applicable to multi-dimensional DHT and DHT inverses.

关键词： Discrete transforms Signal processing algorithms Digital signal processing Systolic arrays Laboratories educational technology Very large scale integration Hardware Mobile communication Mobile computing

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High performance word level sequential and parallel coding methods and architectures for bit plane coding

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Science in China(Series F) 2008年第4期51卷 337-351页

作者： XIONG ChengYi TIAN JinWen LIU Jian College of Electronic Information Engineering South-Central University for Nationalities Wuhan 430074 China Institute of Pattern Recognition & Artificial Intelligence Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science & Technology Wuhan 430074 China

This paper introduced a novel high performance algorithm and VLSI architectures for achieving bit plane coding （BPC） in word level sequential and parallel mode. The proposed BPC algorithm adopts the techniques of coding pass prediction and parallel ＆ pipeline to reduce the number of accessing memory and to increase the ability of concurrently processing of the system, where all the coefficient bits of a code block could be coded by only one scan. A new parallel bit plane architecture （PA） was proposed to achieve word-level sequential coding. Moreover, an efficient high-speed architecture （HA） was presented to achieve multi-word parallel coding. Compared to the state of the art, the proposed PA could reduce the hardware cost more efficiently, though the throughput retains one coefficient coded per clock. While the proposed HA could perform coding for 4 coefficients belonging to a stripe column at one intra-clock cycle, so that coding for an NxN code-block could be completed in approximate N2/4 intra-clock cycles. Theoretical analysis and experimental results demonstrate that the proposed designs have high throughput rate with good performance in terms of speedup to cost, which can be good alternatives for low power applications.

关键词： bit plane coding high performance word-level sequential multi-word parallel

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A no-reference ringing metrics for images deconvolution

A no-reference ringing metrics for images deconvolution

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International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR)

作者： Bo-Xin Zuo Jin-Wen Tian De-Lie Ming State Key Laboratory of Education Commission for Image Processing and Intelligent Control Institute For Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

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.

关键词： image restoration Gabor filters image edge detection Oscillators Deconvolution Maximum likelihood detection Band pass filters

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The Application of A Novel Target Region Extraction Model Based on Object-Accumulated Visual Attention Mechanism

The Application of A Novel Target Region Extraction Model Ba...

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International Conference on Natural Computation (ICNC)

作者： Jie Xiao Chao Cai Mingyue Ding Chengping Zhou Institute of Pattern Recognition and Artificial Intelligence State Education Commission Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

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.

关键词： Data mining Object detection Computer applications Chaos Pattern recognition Artificial intelligence Laboratories image processing Intelligent control Airports

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Dim small targets fusion detection in infrared image

Dim small targets fusion detection in infrared image

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Yu-Qiu Sun Yu Zheng Jin-Wen Tian Jian Liu School of Information and Mathematics Yangtze University Jingzhou China State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China State Education Commission Key Laboratory for Image Processing and Intelligent Control Department of Electronic Information and Enginery of Huazhong University of Science and Technology Wuhan China

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.

关键词： Fractals Wavelet transforms Pixel Object detection Fuses Approximation methods Manganese

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image denoising algorithm based on noise detection

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Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial intelligence 2008年第3期21卷 298-302页

作者： Jin, Liang-Hai Li, De-Hua State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong Univ. of Sci. and Technol. Wuhan 430074 China

An efficient image denoising algorithm is introduced. Firstly, image pixels are classified into noisy pixels and noise-free pixels by four directional operators. Then an adaptive weighted median filter is designed to remove and restore the detected noisy pixels and keep the noise-free ones unchanged. Experimental results indicate that the proposed algorithm preserves image details well while removing impulsive noise efficiently, and its filtering performance is significantly superior to the classical median filter and some other typical and recently developed improved median filters.

关键词： Median filters

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