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检索条件"任意字段=MIPPR 2007: Automatic Target Recognition and Image Analysis;and Multispectral Image Acquisition"

共 165 条记录，以下是11-20 订阅

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Fast approach to super-resolution image reconstruction

Fast approach to super-resolution image reconstruction

引用

mippr 2007: automatic target recognition and image analysis;and multispectral image acquisition

作者： Zhang, Di Hu, Weiping He, Jiazhong Du, Minghui Department of Computer Science Shaoguan University College of Electronics and Information South China University of Technology

ISBN: (纸本)9780819469502

Super-resolution image reconstruction produces a high-resolution image or high- resolution image sequences from a set of shifted, blurred, and decimated versions thereof, and has been proven to be extremely useful in early vision, video surveillance, and other applications. However, as magnification increases, previously published techniques get worse either in computational complexity or ringing artifacts. In this paper, a fast approach is proposed to reduce both the ringing artifacts and the computational complexity. Experiment results demonstrate that the new approach is more efficient and can provide much better reconstruction quality in comparison with normal super-resolution algorithms.

关键词： image resolution

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Difference-templates based target tracking method

Difference-templates based target tracking method

引用

mippr 2007: automatic target recognition and image analysis;and multispectral image acquisition

作者： Luo, Haibo Shi, Zelin Li, Deqiang Yan, Zhande Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Graduate School Chinese Academy of Sciences Beijing 100039 China

ISBN: (纸本)9780819469502

This paper proposes a difference-templates based target tracking method (DTBTTM) with the originality of constructing a collection of difference templates that represent the varying characteristics of target region, such as translation, scale, and illumination. DTBTTM method uses the linear combination of such difference templates to represent the variation of target region, and computes coefficients with respect to the corresponding templates. The final target position and window size can be determined with these coefficients. DTBTTM method simply solves linear equations, and is quite different from correlation method in which 2-dimensional search is required to calculate similarity between pre-defined template and the region of interest. Experimental results show that the DTBTTM is highly adaptable to the variation of target region, and is robust to the variation of translation, scale, illumination, and even occlusion.

关键词： target tracking

来源：评论

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Algorithm of image fusion based on finite ridgelet transform

Algorithm of image fusion based on finite ridgelet transform

引用

mippr 2007: automatic target recognition and image analysis;and multispectral image acquisition

作者： Liu, Kun Guo, Lei Chang, Weiwei Li, Huihui College of Automation Northwestern Polytechnical University Xi'an 710072 China

ISBN: (纸本)9780819469502

Finite ridgelet transform (FRIT) overcomes the weakness of wavelet transform representing in two or higher dimensions and FRIT can efficiently represent the singularity of linear in image. When FRIT is applied to image fusion, the characters of original images can be effectively extracted and more important information is preserved. In this paper, we discussed the advantage of FRIT applying to the image fusion and the process of the fusion algorithm based on FRIT in details. Two sets of images are taken as experimental data, subjective and objective standard are used to evaluate the results. The experiment results show that the FRIT algorithm gets much better fusion results than wavelet, and image fusion algorithm based on FRIT is an effective and feasible algorithm.

关键词： image fusion

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analysis of wavelet image denoising model in Besov spaces

Analysis of wavelet image denoising model in Besov spaces

引用

mippr 2007: automatic target recognition and image analysis;and multispectral image acquisition

作者： Fan, Qibin Jiang, Minkai Xiao, Wenping School of Mathematics and Statistics Wuhan University Wuhan 430072 China

ISBN: (纸本)9780819469502

In this paper, we discuss the image denoising model which DeVore et al. had established, in which both distance and smoothness can be measured by the objective function, and analysis the model for wavelet image denoising in the Besov spaces with p = q . In addition, we give the exact thresholds for the model, and prove that for 0 < p < 1 the effect of noise removal using our methods is in between hard wavelet shrinkage and soft wavelet shrinkage. For the case 0 < p < 1 and 1 < p < ∞, which refers to the problems on the convergence of the iteration of the equations and on the complexity of computation, we give the simplified algorithms. Comparing the threshold given by this paper with Lorenz threshold, we conclude that the former is more meticulous than the latter for the model.

关键词： image processing

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Method of image enhancing based on shape feature of target

Method of image enhancing based on shape feature of target

引用

mippr 2007: automatic target recognition and image analysis;and multispectral image acquisition

作者： Wu, Wei Xiang, Lan Zhou, Zude School of Information Engineering Wuhan University of Technology

ISBN: (纸本)9780819469502

It is difficult to get ideal effect that research on target enhancement and segmentation are developed by simply using features of edge, texture and gray in complex background. Studies on target enhancement and segmentation have always been the research focus for a long time. Considering known regular shape target in complex background, an approach of target enhancement and segment based on shape feature is proposed. According to analyze the shape of regular target such as line and arc, first, Top-hat is used to enhance target. Then, threshold segmentation method, thinning and deburring are following. Third, a new image is acquired by the Hough transform which can find points in edge image similar with target in shape and property. The very points would be reserved. Moreover, the new image acquired is the initial condition of reconstruction, the original image is limit condition, and target enhancement is achieved by grayscale morphological reconstruction. Finally, binaryzation processing of image was used to segment target. Experimental results demonstrate that the proposed algorithm has an encouraging performance.

关键词： image enhancement

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Novel adaptive multi threshold image segmentation algorithm

Novel adaptive multi threshold image segmentation algorithm

引用

mippr 2007: automatic target recognition and image analysis;and multispectral image acquisition

作者： Hong, Jiang Zhang, Ren School of Automation Science and Electrical Engineering BeiHang University Beijing 100083 China

ISBN: (纸本)9780819469502

A novel adaptive multi threshold image segmentation algorithm is proposed in this paper. This proposed segmentation algorithm has two unique characteristics: it fits the 1-D graylevel histogram of the image by potential base function and thereby adaptively determines the classification number by potential function clustering;based on the graylevel co-occurrence matrix, it acquires the multi segmentation thresholds which makes the shape connectivity maximum according to the shape connectivity criterion. Both theoretical analysis and simulation results indicate that the performance of this new adaptive multi threshold segmentation algorithm is superior to those of the conventional threshold segmentation algorithms. And it has not only a low computing cost, but also shows quite good segmentation effect. Besides, it is insensitive to noises and interferences.

关键词： Adaptive algorithms

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FLIR image segmentation based on DA-GMRF model

FLIR image segmentation based on DA-GMRF model

引用

mippr 2007: automatic target recognition and image analysis;and multispectral image acquisition

作者： Qi, Lin Shi, Zelin Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Graduate School Chinese Academy of Sciences Beijing 100039 China

ISBN: (纸本)9780819469502

In order to conquer the drawback of over-smoothness in the MRF model, a kind of discontinuity-adaptive Gaussian Markov random field (DA-GMRF) model is defined, in which the edge information of image is used to construct corresponding energy functions. After this a FLIR image segmentation method based on DA-GMRF model is proposed, which includes initialization and optimization of the label field. A multi-threshold image segmentation algorithm based on potential function of gray histogram is presented to initialize the label field. This algorithm can determine region number and multi-thresholds automatically. Metroplis Sampler algorithm is adopted to optimize the label field. Segmentation experiments on several images show that the algorithm proposed is effective.

关键词： image segmentation

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Edge detection operators applications in flame image recognition and processing - art. no. 67864R

Edge detection operators applications in flame image recogni...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Shao, Ying Huazhong Univ Sci & Technol Wuhan 430070 Peoples R China

Based on region-segmentation method and flame image edge detection operator, flame image pre-processing and edge detection can effectively improve flame image processing efficiency. Relatively effective flame image ed... 详细信息

ISBN: (纸本)9780819469502

关键词： fire detection image processing region-segmentation edge detection operator

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Application of SGNN-based method in image segmentation

Application of SGNN-based method in image segmentation

引用

mippr 2007: automatic target recognition and image analysis;and multispectral image acquisition

作者： Li, Lu Jiang, Hong Ren, Zhang Zhang, Yong-Fei School of Automation Science and Electrical Engineering Beihang University Beijing 100083 China

ISBN: (纸本)9780819469502

In this paper, a SGNN (Self-Generating Neural Network)-based method is applied to image segmentation, which is implemented automatically by autonomously clustering the pixels according to their gray values. The optimization of SGNN is studied to further improve the accuracy and robustness, as well as to reduce the computational complexity of the segmentation. The experimental results show that the optimized SGNN gets better segmentation results and outperforms the existing methods for its distinguished advantages of perfect segmentation without any manual intervention, high self-learning capacity, less computational complexity, robustness to noise, etc. What's more, the experimental results suggest that the proposed method can be widely used in segmentation of all typical images, such as IR (Infrared) images, visible images, X-ray images, and MR (Magnetic Resonance) images.

关键词： image segmentation

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Error analysis on laser measurement device of airborne LIDAR

Error analysis on laser measurement device of airborne LIDAR

引用

mippr 2007: automatic target recognition and image analysis;and multispectral image acquisition

作者： Jianwei, Wu Hongchao, Ma Qi, Li Zongyue, Wang Xin, Yu School of Remote Sensing Information Engineering Wuhan University 129 Luoyu Road Wuhan 430079 China

ISBN: (纸本)9780819469502

The error sources of airborne laser measurement device which mainly include laser beam misalignment with respect to scanning mirror, clock error, scanner error and scanner torsion are discussed, and their effects to airborne LIDAR (Light Detection and Ranging) position accuracy are analyzed. Specially, laser beam misalignment's influences to LIDAR scanning line distortion and positioning accuracy are analyzed in detail quantitatively and qualitatively for oscillating scanner. The analysis demonstrates that laser beam misalignment influences the scanning line distortion and positioning accuracy more and more with the increasing height and scanning angle and can't be eliminated by common calibration methods but by the calibration method in factory for it is related to other error sources.

关键词： Optical radar

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