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检索条件"机构=Laboratory for Image Processing and Intelligent Control"

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Robust ICA neural network and application on Synthetic Aperture Radar (SAR) image analysis

引用

13th International Conference on Neural Information processing, ICONIP 2006

作者： Jian, Ji Zheng, Tian Department of Computer Science and Technology Northwestern Polytechnical University Xi'an 710072 China Department of Applied Mathematics Northwestern Polytechnical University Xi'an 710072 China Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)3540464816

Independent component analysis (ICA) has shown success in the separation of sources in lots of applications. However, in synthenic aperture radar (SAR) images the noise is multiplicative, so the applicability of ICA is seriously reduced. This paper proposes a new robust independent component analysis neural network (RICANN) that improves the robustness of ICA by adding outlier rejection rule. Its application in synthetic aperture radar (SAR) is discussed. The results show the potential usage in SAR image processing problems. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Synthetic aperture radar

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Dim Small Targets Detection Based on Dualband Infrared image Fusion

Dim Small Targets Detection Based on Dualband Infrared Image...

引用

IEEE International Conference on Industrial Technology (ICIT)

作者： Yu-Qiu Sun Jin-Wen Tian Jian Liu State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recongnition and Artificial Intelliegence Huazhong University of Science and Technology Wuhan China School of Information and Mathematics Yangtze University Jingzhou China State Education Commission Key Laboratory for Image Processing and Intelligent Control Department of Electronic Information and Enginery 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 thresholding. The experimental results show that the method using fractal dimension to fuse dualband infrared images, and then detect targets is superior to use mid-wave or long -wave infrared images detect targets alone.

关键词： Object detection Dual band Infrared imaging Infrared detectors image fusion Fuses Fractals Concrete Shape Wavelet domain

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Contrast-modulated Nonlinear Diffusion for X-ray Angiogram images

Contrast-modulated Nonlinear Diffusion for X-ray Angiogram I...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Baopu Li Nong Sang Zhiguo Cao Department of Electronic Engineering Chinese University of Hong Kong Sha Tin Hong Kong China Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Wuhan China

In this paper, we present a new method for X-ray angiogram images enhancement using a contrast-modulated nonlinear diffusion. The original nonlinear diffusion is gradient driven, which leads into much dependence on the accurate estimation of the edge. However, it is very difficult to get the accurate estimation of edges for X-ray angiogram images, which are characterized with complex background. So it is necessary to do some improvements to this model. By designing a new concept of contrast space according to the characteristics of these images, we change the original nonlinear diffusion into contrast-modulated nonlinear diffusion. Compared with the traditional method, this new approach is proved to have a better performance of enhancement

关键词： X-ray imaging Anisotropic magnetoresistance image processing image analysis control engineering education intelligent control image enhancement Biomedical imaging Medical diagnostic imaging Chemicals

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Dualband Infrared images Target Detection Algorithm Based on Multiscale Morphology

Dualband Infrared Images Target Detection Algorithm Based on...

引用

2006 8th International Conference on Signal processing

作者： Yuqiu Sun Jinwen Tian Jian Liu School of Information and Mathematics Yangtze University State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial IntelligenceHuazhong University of Science and Technology

According to the features of mid-wave and long-wave infrared images,they are decomposed into morphology pyramid respectively based on the new multiscale mathematical morphology filters proposed in the *** features such as local maximum gray level and average gradient strength of every image are extracted at each level of morphology *** dualband infrared images based on fusion rule put forward in the paper,and then reconstruct original image and detect target using contrast threshold *** experiment results show that dualband infrared images target detection algorithm based on multiscale morphology algorithm is better than use mid-wave or long-wave infrared images detect targets alone.

关键词： image Dualband Infrared images Target Detection Algorithm Based on Multiscale Morphology Target

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A DSP/FPGA - Based Parallel Architecture for Real-time image processing

A DSP/FPGA - Based Parallel Architecture for Real-time Image...

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World Congress on intelligent control and Automation (WCICA)

作者： Luxin Yan Tianxu Zhang Sheng Zhong Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

A DSP/FPGA-based parallel architecture oriented to real-time image processing applications is presented. The architecture is structured with high performance DSPs interconnected by FPGA. Within FPGA a FIFO interconnection network and the specific data communication protocol are implemented, which interconnect 3 DSPs (TMS320C6414) effectively. The measured performances in the prototype with the proposed parallel architecture, including inter-DSP data communication performance and system computing capacity, show high data transfer bandwidth (up to 400 Mbytes/s) with low latency as well as high image processing performance, which achieve a good balance for parallel image processing

关键词： Digital signal processing Field programmable gate arrays Parallel architectures image processing Data communication Computer architecture Multiprocessor interconnection networks Protocols Performance evaluation Prototypes

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A Combining Method for Tumors Detection from Near-infrared Breast Imaging

A Combining Method for Tumors Detection from Near-infrared B...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Zhicheng Wang Jian Liu Jinwen Tian Zeping Xie State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong Univ. of Sci. & Tech. Wuhan 430074 China Key Lab. for Image Process. & Intelligent Control State Educ. Comm. School of Life Science & Technology Huazhong University of Science and Technology Wuhan China

This paper introduces the new qualitative and quantitative methods, which can diagnose breast tumors. Qualitative methods include blood vessel display inside and outside of pathological changes part of breast, display of equivalent pixel curves at the part of pathological changes and display of breast tumor image edge. Accordingly, three feature extraction operators are proposed, i.e. the combination operators of anisotropic gradient and smoothing operator, an improved Sobel operator and an edge sharpening operator. Furthermore, quantitative diagnostic approaches are discussed based on blood and oxygen contents according to abundant clinical data and pathological mechanism of breast tumors. The results of clinic show that the methods of combining qualitative and quantitative diagnose are effective for breast tumor images, especially for early and potential breast cancer

关键词： Breast tumors Displays Pathology Blood vessels Biomedical imaging Pixel Feature extraction Anisotropic magnetoresistance Smoothing methods Breast cancer

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3D TRUS image Segmentation in Prostate Brachytherapy

3D TRUS Image Segmentation in Prostate Brachytherapy

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Mingyue Ding L. Gardi Zhouping Wei A. Fenster Institute for Pattern Recognition and Artificial Intelligence Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China Imaging Research Laboratories Robarts Research Institute London ONT Canada

Brachytherapy is a minimally invasive interventional surgery used to treat prostate cancer. It is composed of three steps: dose pre-planning, implantation of radioactive seeds, and dose post-planning. In these procedures, it is crucial to determine the positions of needles and seeds, measure the volume of the prostate gland. Three-dimensional transrectal ultrasound (TRUS) imaging has been demonstrated to be a useful technique to perform such tasks. Compared to CT, MRI or X-ray imaging, US image suffers from low contrast, image speckle and shadows, making it challenging for segmentation of needles, the prostates and seeds in the 3D TRUS images. In this paper, we reviewed 3D TRUS image segmentation methods used in prostate brachytherapy including the segmentations of the needles, the prostate, as well as the seeds. Furthermore, some experimental results with agar phantom, turkey and chicken phantom, as well as the patient data are reported

关键词： image segmentation Brachytherapy Needles Minimally invasive surgery Ultrasonic imaging Imaging phantoms Oncological surgery Prostate cancer Position measurement Volume measurement

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Spatially Adaptive Kernels for Adaptive Spatial Filtering of fMRI Data

Spatially Adaptive Kernels for Adaptive Spatial Filtering of...

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International Joint Conference on Neural Networks (IJCNN)

作者： V. Taimouri G.-A. Hossein-Zadeh H. Soltanian-Zadeh Control and Intelligent Processing Centre of Excellence ECE Department Faculty of Engineering University of Tehran Tehran Iran School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics and Medical Image Analysis Laboratory Henry Ford Health System Detroit MI USA

Making use of neighborhood time series is an effective way of noise reduction in fMRI data. However the conventional averaging methods blur activated areas. In this paper, a filter with adaptive kernel is designed such that its kernel size and direction are defined at each voxel. First, for finding the optimum size of kernel, a linear combination of some isotropic Gaussian filters with different variances is used, and optimum value of variance is specified. Then, the appropriate kernel direction is determined by a linear combination of some anisotropic basic filters with various directions. The weights of these linear combinations can be calculated by using the restricted canonical correlation method. The proposed method is compared with a similar method based on the steerable filters and the results show that the proposed method improves the ROC curve and prohibits false spread of the activation areas.

关键词： Kernel Adaptive filters Filtering Nonlinear filters Anisotropic magnetoresistance Magnetic separation Process control intelligent control Correlation Magnetic resonance imaging

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Rule-based decision-making framework for knowledge-based anatomical landmark localization (K-BALL)

Rule-based decision-making framework for knowledge-based ana...

引用

IEEE International Symposium on Biomedical Imaging

作者： M.-R. Siadat H. Soltanian-Zadeh K. Elisevich Henry Ford Health System Radiology Image Analysis Laboratory Detroit MI USA Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Neurosurgery Henry Ford Health System Detroit MI USA

K-BALL is a general method for localization of anatomical phenomena of the same origin with natural discrepancies distributed over a reference space, e.g., human brain anatomical structures. In this paper, we focus on information analysis step (2nd step) of K-BALL during which landmarks extracted in its first step are evaluated. We provide a framework in which rules are automatically generated based on estimated and derived models. We show that the rules based on the derived models can improve the overall success rate of K-BALL. Each rule evaluates the extracted points by producing an intermediate confidence factor (ICNF). A total confidence factor is calculated using ICNF's to facilitate the acceptance or rejection of a set of points as landmarks of interest. Using the rules merely based on the estimated models, simulation study produced an overall success rate of 91.8%. Using the rules based on both of the estimated and derived models, this rate increased to 92.5%

关键词： Decision making Hippocampus Information analysis Data mining Humans Radiology image analysis Radio control Process control control systems

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A support value transform-based multi focus image fusion method

A support value transform-based multi focus image fusion met...

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International Conference on Signal processing Proceedings (ICSP)

作者： Sheng Zheng Jian Liu Guangxi Zhu Jinwen Tian Electronic & Information Engineering Department Huazhong University of Science and Technology Wuhan China College of Electrical Engineering & Information Technology China Three Gorges University Yichang China State Edu Commission Key Laboratory for Image Processing & Intelligent Control HUST Wuhan China Chinese Key laboratory of optic & electronics HUST Wuhan China

The image fusion is an important approach to produce a single complete image which preserves all relevant information from different sensors. In this paper, we proposed a support value transform-based multi focus image fusion method, where the fused saliency features are represented by support values. Based on the mapped least squares support vector machine, the support value transform is developed as a multi-scale analysis tool. The fusing results on the multi focus images demonstrate that the proposed image fusion method is effective and efficient

关键词： Focusing image fusion Support vector machines Discrete wavelet transforms Optical sensors image sensors Sensor fusion Support vector machine classification image processing Least squares methods

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