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A novel image fusion approach based on wavelet transform and fuzzy logic

INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION processing 2006年第4期4卷 617-626页

作者： Li, Tao Liu, Jian Wang, Zhicheng Huazhong Univ Sci & Technol Key Lab Educ Minist Image Proc & Intelligent Control Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Dept Elect & Informat Sci Wuhan 430074 Peoples R China

Better understanding of the real world can be obtained by fusion of images with complementary information. It was shown that an image fusion technique based on wavelet decomposition seems to be a better trade-off between spectral and spatial information in a single image. This paper presents a novel image fusion scheme that is based on wavelet transform and fuzzy logic. The two source images are first decomposed using the discrete wavelet transformation (DWT). Then different rules are used for different components in the fusion procedure. Local average energy is utilized as the fusion parameter for the low frequency component first;then membership degree of wavelet transform coefficient is used as the fusion parameter for the high frequency parts;finally, the fused image is obtained by taking inverse wavelet transform from the combined coefficients. The proposed fusion approach is shown to be effective using some remote sensing test images.

关键词： image fusion fuzzy logic membership function wavelets transform

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TARGET RECOGNITION USING BAYESIAN DATA FUSION METHOD

TARGET RECOGNITION USING BAYESIAN DATA FUSION METHOD

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2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

作者： YU-QIU SUN JIN-WEN TIAN JIAN LIU School of Information and Mathematics Yangtze University Jingzhou 434023 China State Education Co State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute fo State Education Commission Key Laboratory for Image Processing and Intelligent Control Dept.of Elec

Multisensor information plays an important pole in the target recognition and other application fields. Fusion performance is tightly depended on the fusion level selectes and the approach used. Feature level fusion is a potential and difficult fusion level. Bayesian fusion method is an important theory in feature level. A new method is presented to fuse infrared images and recognize object in the paper. Firstly,Bayesian principles, fusion mode and recognition decision function are described. Then, aiming at the features of mid-wave infrared image and long-wave infrared image, we use Bayesian probability to fuse them. Last, recognize target and background obtained with training and test pattern vectors. The experiment results show stability and feasibility of the fusion recognition using Bayesian decision theory in infrared image.

关键词： Bayesian decision data fusion target recognition infrared images

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Extraction of salient contours via excitatory-inhibitory interactions in the visual cortex

Extraction of salient contours via excitatory-inhibitory int...

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7th Asian Conference on Computer Vision

作者： Tang, QL Sang, N Zhang, TX Huazhong Univ Sci & Technol Inst Pattern Recognit & Artificial Intelligence Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Minist Educ Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

ISBN: (纸本)3540312447

In this paper we mimic a biological visual strategy to extract salient contours from complex scenes. Psychophysical and physiological studies show that the response to the stimulus within the receptive field is affected by the presence of surrounding stimuli- the response is suppressed significantly by similarly oriented stimuli in the surround while this suppression is converted to strong facilitation with the addition of collinear stimuli in the surround. According to this property of visual perception, we enhance salient contours and at the same time reduce the interference of the extraneous elements. Our results show the feasibility of the proposed method.

关键词： Computer vision

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Speckle reduction of polarimetric SAR images based on neural ICA

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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

The polarimetric synthetic aperture radar (PSAR) images are modeled by a mixture model that results from the product of two independent models, one characterizes the target response and the other characterizes the speckle phenomenon. For the scene interpretation, it is desirable to separate between the target response and the speckle. For this purpose, we proposed a new speckle reduction approach using independent component analysis (ICA) based on statistical formulation of PSAR image. In addition, we apply four ICA algorithms on real PSAR images and compare their performances. The comparison reveals characteristic differences between the studied neural ICA algorithms, complementing the results obtained earlier. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Synthetic aperture radar

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

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13th International Conference on Neural Information processing, ICONIP 2006

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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3D ultrasound image guidance system used in RF uterine adenoma and uterine bleeding ablation system

3D ultrasound image guidance system used in RF uterine adeno...

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Medical Imaging 2006 Conference

作者： Ding, Mingyue Luo, Xiaoan Cai, Chao Zhou, Chengping Fenster, Aaron Huazhong Univ Sci & Technol Inst Pattern Recognit & Artificial Intelligence Image Proc & Intelligent Control Key Lab Educ Minist Wuhan 430074 Peoples R China Robarts Res Inst London ON N6A 5K8 Canada

ISBN: (纸本)0819461849

Uterine adenoma and uterine bleeding are the two most prevalent diseases in Chinese women. Many women lose their fertility from these diseases. Currently, a minimally invasive ablation system using an RF button electrode is being used in Chinese hospitals to destroy tumor cells or stop bleeding. In this paper, we report on a 3D US guidance system developed to avoid accidents or death of the patient by inaccurate localization of the tumor position during treatment. A 3D US imaging system using a rotational scanning approach of an abdominal probe was built. In order to reduce the distortion produced when the rotational axis is not collinear with the central beam of the probe, a new 3D reconstruction algorithm is used. Then, a fast 3D needle segmentation algorithm is used to find the electrode. Finally, the tip of electrode is determined along the segmented 3D needle and the whole electrode is displayed. Experiments with a water phantom demonstrated the feasibility of our approach.

关键词： needle segmentation 3D ultrasound RF ablation line segment detection

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Dim Small Targets Detection Based on Dualband Infrared image Fusion

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

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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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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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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...

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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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