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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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An Improved Landweber Method for Restoration of Aero-Optically Degraded images

An Improved Landweber Method for Restoration of Aero-Optical...

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International Conference on Computer science and Software Engineering

作者： Wenxia Yang Chao Cai Mingyue Ding Chengping Zhou Key Laboratory for Image Processing and Intelligence Control of the Ministry of Education Institute of IPRAI Huazhong University of Science and Technology Wuhan China Department of Mathematics Wuhan University of Technology Wuhan China

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.

关键词： image restoration Degradation Infrared imaging Aircraft Educational technology Infrared sensors Computer science Software engineering Chaos Laboratories

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TerraSAR-X: Complex image Inversion for Feature Extraction

TerraSAR-X: Complex Image Inversion for Feature Extraction

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Matteo Soccorsi Mihai Datcu Dusan Gleich German Aerospacec Center Remote Sensing Technology Institute Wessling Germany Laboratory for Signal Processing and Remote Control Faculty of Electrical Engineering and Computer Science University of Maribor Slovenia

In this paper we present two algorithms for information extraction from Single Look Complex (SLC) Synthetic Aperture Radar (SAR) images. The first algorithm is based on Tikhonov regularization with Total Variation (TV) and a Point-Based Feature (PBF) term. Based on the equivalence of Tikhonov and the Bayesian estimate, the second algorithm is a Maximum A Posteriori (MAP) estimation with a complex-valued Gauss-Markov Random Field (GMRF) in addition to the TV prior. The first algorithm produces a despeckled image preserving fine details and texture. The second algorithm gives a denoised image and in addition the estimated feature parameter vector thetas.

关键词： Feature extraction Synthetic aperture radar signal processing algorithms TV Bayesian methods image restoration Adaptive filters Cost function Anisotropic magnetoresistance Speckle

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An image enhancement technique in the DCT domain for cancer detection

An image enhancement technique in the DCT domain for cancer ...

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Asilomar Conference on signals, Systems & Computers

作者： Xiaoming Liu Qingling Sun Jinshan Tang College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Image Processing and Bio-imaging Research Laboratory Systems Research Institute Department of Advanced Technologies Alcorn State University Lorman MS USA

In this paper, we develop an image enhancement technology in the DCT domain for radiologists to screen mammograms. The proposed algorithm is an improved version of the algorithm developed. The improved algorithm overcomes the shortcomings of the old algorithm which requires manual adjustment of multiple parameters to realize non-uniform enhancement in different frequency bands. The proposed image enhancement algorithm is expressed as an optimization problem. In the optimization problem, the optimal local enhancement factors are found so that the target global contrast value is achieved which is specified by a user. Because it's a multi-variable optimization problem, genetic algorithm is used to search the optimal parameters. The experimental results show that the algorithm is progressive.

关键词： image enhancement Discrete cosine transforms Cancer detection Breast cancer image coding Mammography image processing Genetic algorithms Wavelet transforms X-ray detection

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An improved WSQ fingerprint image compression algorithm

An improved WSQ fingerprint image compression algorithm

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Asilomar Conference on signals, Systems & Computers

作者： Jinshan Tang Xiaoming Liu College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Image Processing and Bio-Imaging Reasearch Laboratory Systems Research Institute Department of Advanced Technologies Alcorn State University Lorman MS USA

The wavelet/scalar quantization (WSQ) [1] fingerprint image compression algorithm is effective and has been widely applied to fingerprint image compression. However, WSQ cannot control the compression ratio and its performance on fuzzy images is poor. We propose an improved WSQ fingerprint image compression algorithm to overcome the above shortcomings. Our algorithm uses a mixed quantizer so that the algorithm can treat fuzzy and non-fuzzy fingerprint images separately. In order to control the compression ration, an optimization parameters for a specific compression ratio. The proposed algorithm is compared with the traditional WSQ fingerprint image compression algorithm and the results are encouraging.

关键词： Fingerprint recognition image matching Compression algorithms

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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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Needle Segmentation Using 3D Quick Randomized Hough Transform

Needle Segmentation Using 3D Quick Randomized Hough Transfor...

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International Workshop on Intelligent Networks and Intelligent Systems (ICINIS)

作者： Wu Qiu Mingyue Ding Ming Yuchi Institute for Pattern Recognition and Artificial Intelligence Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei China Department of Biomedical Engineering School of Life Science and Technology Huazhong University of Science and Technology Wuhan Hubei China

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.

关键词： Needles image segmentation Electrodes Ultrasonic imaging Intelligent networks Artificial intelligence Educational technology Hemorrhaging Imaging phantoms Radio frequency

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A Comprehensive Comparison of Routing Metrics for Wireless Mesh Networks

A Comprehensive Comparison of Routing Metrics for Wireless M...

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IEEE International Conference on Networking, Sensing and Control

作者： Hui Liu Wei Huang Xu Zhou X. H. Wang School of Communication and Information Engineering University of Electronic Science and Technology China National Laboratory of Radar Signal Processing Xidian University Xi'an China Institute of Advanced Telecommunications Swansea University Swansea UK

It is well-known that finding paths with minimum hop count leads to poor performance in wireless mesh networks (WMN) because the assumption of the same transmission failure probability in all links may not be true. A routing metric can assist traditional routing protocol in selecting better paths by explicitly taking the interference, delay etc. into account. This paper presents a thorough review and a comparison of 10 kinds of routing metrics designed for diverse QoS requirements in WMN. Meanwhile, this paper classifies these routing metrics into three basic types, ETX-based metrics, mETX, and some other metrics less attractive to WMN routing layer, for better understanding and future applications. To the best of our knowledge, no paper except this one has such a comprehensive review of routing metrics utilized in WMN.

关键词： Wireless mesh networks Routing protocols Interference Costs Disaster management Electronic mail Delay Intelligent networks technology management Telecommunication traffic

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Temporal pattern recognition using spiking neural networks for cortical neuronal spike train decoding

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IFAC Proceedings Volumes 2008年第2期41卷 5203-5208页

作者： Huijuan Fang Yongji Wang Jiping He Shan Liu Key Laboratory for Image Processing and Intelligent Control of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China (Tel: 86-27-87557284 The Harrington Department of Bioengineering and the Center for Neural Interface Design of The Biodesign Institute Arizona State University Tempe AZ 85287 USA

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.

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