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检索条件"任意字段=Third International Symposium on Multispectral Image Processing and Pattern Recognition"

共 1067 条记录，以下是251-260 订阅

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Blind Estimation of Affine Transformation Using 2-D Cyclostationarity of Resampled images 9

Blind Estimation of Affine Transformation Using 2-D Cyclosta...

引用

9th international symposium on multispectral image processing and pattern recognition (MIPPR) - multispectral image Acquisition, processing, and Analysis

作者： Ou, Junhai Ni, Jiangqun Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510275 Guangdong Peoples R China Chinese Acad Sci Inst Informat Engn State Key Lab Informat Secur Beijing 100093 Peoples R China

ISBN: (纸本)9781510600522

This paper presents a unified way to estimate the parameters of affine transformation in the absence of original image. With 2-D cyclostationary characterization, we analytically show that the covariance of affine transformed image is periodic with the affine transformation matrix. Based on the relationship between the affine transformation matrix and the position of resampling-caused striking peaks in the 2-D spectrum of the image's edge map, we further study how to estimate the parameters of several typical affine transformations, e.g., the scaling factor, the rotation angle, the joint scaling and rotation transformation parameters. Examples of the output of our algorithm are shown and comparative results are presented to evaluate the performance of the proposed algorithm.

关键词： image forensics resampling detection affine transformation estimation 2-D Cyclostationarity

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Facade model refinement by fusing terrestrial laser data and image 9

Facade model refinement by fusing terrestrial laser data and...

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9th international symposium on multispectral image processing and pattern recognition (MIPPR) - pattern recognition and Computer Vision

作者： Liu Yawen Qin Sushun Wuhan Univ Sch Remote Sensing & Informat Engn 129 Luoyu Rd Wuhan 430079 Hubei Peoples R China

ISBN: (纸本)9781510600546

The building facade model is one of main landscapes of a city and basic data of city geographic information. It is widely useful in accurate path planning, real navigation through the urban environment, location-based application, etc. In this paper, a method of facade model refinement by fusing terrestrial laser data and image is presented. It uses the matching of model edge and image line combined with laser data verification and effectively refines facade geometry model that reconstructed from laser data. The laser data of geometric structures on building facade such as window, balcony and door are segmented, and used as a constraint for further selecting the optical model edges that are located at the cross-line of point data and no data. The results demonstrate the deviation of model edges caused by laser sampling interval can be removed in the proposed method.

关键词： Facade model laser data segmentation model refinement

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A novel algorithm for multi-frame real image restoration 9

A novel algorithm for multi-frame real image restoration

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9th international symposium on multispectral image processing and pattern recognition (MIPPR) - Remote Sensing image processing, Geographic Information Systems, and Other Applications

作者： Hua, Xia Shi, Yu Wuhan Inst Technol Sch Elect & Informat Engn Lab Image Proc Wuhan 430074 Peoples R China

ISBN: (纸本)9781510600560

We present a novel blind restoration algorithm to restore object images from real images based on maximum likelihood estimation. In order to estimate the unknown turbulence point spread functions (PSF) of the observed image contain the same objects, multi-frame images are used to construct an integral likelihood function. A series of experiments for synthetic and real images illustrate that the proposed algorithm is effective in restoring real images.

关键词： turbulence-degraded image multi-frame image restoration maximum likelihood estimation

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Research of Adaptive Threshold Edge Detection Algorithm Based on Statistics Canny Operator 9

Research of Adaptive Threshold Edge Detection Algorithm Base...

引用

9th international symposium on multispectral image processing and pattern recognition (MIPPR) - Automatic Target recognition and Navigation

作者： Xu, Jian Wang, Huaisuo Huang, Hua Hubei Univ Nationalities Coll Sci & Technol Enshi 445000 Peoples R China Sichuan Univ Sch Elect Engn & Informat Chengdu 610065 Peoples R China

ISBN: (纸本)9781510600539

The traditional Canny operator cannot get the optimal threshold in different scene, on this foundation, an improved Canny edge detection algorithm based on adaptive threshold is proposed. The result of the experiment pictures indicate that the improved algorithm can get responsible threshold, and has the better accuracy and precision in the edge detection.

关键词： Imagine processing Edge detection Canny operator Adaptive threshold

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Super pixel density based clustering automatic image classification method 9

Super pixel density based clustering automatic image classif...

引用

9th international symposium on multispectral image processing and pattern recognition (MIPPR) - Automatic Target recognition and Navigation

作者： Xu, Mingxing Zhang, Chuan Zhang, Tianxu Huazhong Univ Sci & Technol Natl Key Lab Sci & Technol Multispectral Informat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Automat Wuhan 430074 Peoples R China

ISBN: (纸本)9781510600539

The image classification is an important means of image segmentation and data mining, how to achieve rapid automated image classification has been the focus of research. In this paper, based on the super pixel density of cluster centers algorithm for automatic image classification and identify outlier. The use of the image pixel location coordinates and gray value computing density and distance, to achieve automatic image classification and outlier extraction. Due to the increased pixel dramatically increase the computational complexity, consider the method of ultra-pixel image preprocessing, divided into a small number of super-pixel sub-blocks after the density and distance calculations, while the design of a normalized density and distance discrimination law, to achieve automatic classification and clustering center selection, whereby the image automatically classify and identify outlier. After a lot of experiments, our method does not require human intervention, can automatically categorize images computing speed than the density clustering algorithm, the image can be effectively automated classification and outlier extraction.

关键词： image classification super-pixel density clustering automated classification

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A modified JPEG-LS lossless compression method for remote sensing images 9

A modified JPEG-LS lossless compression method for remote se...

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9th international symposium on multispectral image processing and pattern recognition (MIPPR) - Remote Sensing image processing, Geographic Information Systems, and Other Applications

作者： Deng, Lihua Huang, Zhenghua Huazhong Univ Sci & Technol Sch Automat Natl Key Lab Sci & Tech Multispectral Informat Pr Wuhan 430074 Peoples R China Three Gorges Univ Coll Comp & Informat Technol Yichang 443002 Hubei Peoples R China

ISBN: (纸本)9781510600560

As many variable length source coders, JPEG-LS is highly vulnerable to channel errors which occur in the transmission of remote sensing images. The error diffusion is one of the important factors which infect its robustness. The common method of improving the error resilience of JPEG-LS is dividing the image into many strips or blocks, and then coding each of them independently, but this method reduces the coding efficiency. In this paper, a block based JPEP-LS lossless compression method with an adaptive parameter is proposed. In the modified scheme, the threshold parameter RESET is adapted to an image and the compression efficiency is close to that of the conventional JPEG-LS.

关键词： JPEG-LS image compression error diffusion lossless compression remote sensing image

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Classification of PolSAR image based on quotient space theory 9

Classification of PolSAR image based on quotient space theor...

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9th international symposium on multispectral image processing and pattern recognition (MIPPR) - multispectral image Acquisition, processing, and Analysis

作者： An, Zhihui Yu, Jie Liu, Xiaomeng Liu, Limin Jiao, Shuai Zhu, Teng Wang, Shaohua Capital Normal Univ Coll Resources Environm & Tourism Beijing 100048 Peoples R China Capital Normal Univ Beijing Key Lab Resource Environm & Geog Informat Beijing 100048 Peoples R China Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan 430079 Peoples R China

ISBN: (纸本)9781510600522

In order to improve the classification accuracy, quotient space theory was applied in the classification of polarimetric SAR (PolSAR) image. Firstly, Yamaguchi decomposition method is adopted, which can get the polarimetric characteristic of the image. At the same time, Gray level Co-occurrence Matrix (GLCM) and Gabor wavelet are used to get texture feature, respectively. Secondly, combined with texture feature and polarimetric characteristic, Support Vector Machine (SVM) classifier is used for initial classification to establish different granularity spaces. Finally, according to the quotient space granularity synthetic theory, we merge and reason the different quotient spaces to get the comprehensive classification result. Method proposed in this paper is tested with L-band AIRSAR of San Francisco bay. The result shows that the comprehensive classification result based on the theory of quotient space is superior to the classification result of single granularity space.

关键词： polarimetric SAR quotient space granularity synthetic and reasoning image classification

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A new method of extracting region of interest image area with L0 norm 9

A new method of extracting region of interest image area wit...

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9th international symposium on multispectral image processing and pattern recognition (MIPPR) - Automatic Target recognition and Navigation

作者： Zhang, Yaozong Zhang, Chuan Xu, Mingxin Huazhong Univ Sci & Technol Sci & Technol Multispectral Informat Proc Lab Sch Automat Wuhan 430074 Hubei Peoples R China

ISBN: (纸本)9781510600539

The process of Reference image preparation, is to extract region of interest area from a image, to get a simplified image which be used as template image for other algorithms. Because of the complex of scene, one usually need to excute a set of different algorithms to get a final image which only has the information of interest area. This paper presents a new variational model which used L0 norm for fidelity item, to keep information of interested area better, while removing other redundant information. Experiments show that, this method can remove information of grediant in some special range, to handle a more general case, compared with the original L0 gradient method which can only remove low frequency information. Compared with the same variational model but using L1 or L2 norm, the proposed method can well retain the original information. Those advantages is very important for making the process of reference image preparation faster and easier.

关键词： L0 norm variational model reference image preparation interest area

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Evaluation of Multiple and Multiscale Morphological Profiles on the Classification of Hyperspectral image 9

Evaluation of Multiple and Multiscale Morphological Profiles...

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9th international symposium on multispectral image processing and pattern recognition (MIPPR) - multispectral image Acquisition, processing, and Analysis

作者： Cao, XiaoWang Zhao, Wenfei Wang, Leiguang Southwest Forestry Univ Sch Forestry Kunming 430079 Peoples R China

ISBN: (纸本)9781510600522

Hyperspectral data sets with high spatial resolution have been widely used in the research of image classification. The methodology based on the mathematical morphology, which aims at extracting the structure of hyperspectral images, has been implemented. In this method, opening and closing morphological operation used in hyperspectral data in order to retain spatial information of objects. Morphological profiles are established based on opening and closing transforms with structure element of different size. The proper definition of structure elements is the key of extracting morphological features for the image classification. Which kind of structural element is better for image classification. Can be discussed the classification results by setting different structural element to extract morphological features. In the experiments, we have defined four types of structure element to extract spatial features. Later on, the features are fed into a support vector machine (SVM) classifier respectively. The influence of different types of structure elements is judged by the classification accuracy. The experiment results illustrates disk shape of structural element is superior to diamond shape of structural element and the structural elements of large radius is better than the structural elements of small radius.

关键词： Hyperspectral data morphological profiles structure element erosion dilation opening operation closing operation classification

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A Novel Scatter-Matrix Eigenvalues-Based Total Variation(SMETV) Regularization for Medical image Restoration 9

A Novel Scatter-Matrix Eigenvalues-Based Total Variation(SME...

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9th international symposium on multispectral image processing and pattern recognition (MIPPR) - Parallel processing of images and Optimization;and Medical Imaging processing

作者： Huang, Zhenghua Zhang, Tianxu Deng, Lihua Fang, Hao Li, Qian Huazhong Univ Sci & Technol Inst Pattern Recognit & Artificial Intelligence Sci & Technol Multispectral Informat Proc Lab Wuhan 430074 Peoples R China Wuhan Donghu Univ Wuhan 430074 Peoples R China South Cent Univ Nationalities Coll Biomed Engn Wuhan 430074 Peoples R China

ISBN: (纸本)9781510600553

Total variation(TV) based on regularization has been proven as a popular and effective model for image restoration, because of its ability of edge preserved. However, as the TV favors a piece-wise constant solution, the processing results in the flat regions of the image are easily produced "staircase effects", and the amplitude of the edges will be underestimated;the underlying cause of the problem is that the regularization parameter can not be changeable with spatial local information of image. In this paper, we propose a novel Scatter-matrix eigenvalues-based TV(SMETV) regularization with image blind restoration algorithm for deblurring medical images. The spatial information in different image regions is incorporated into regularization by using the edge indicator called difference eigenvalue to distinguish edges from flat areas. The proposed algorithm can effectively reduce the noise in flat regions as well as preserve the edge and detailed information. Moreover, it becomes more robust with the change of the regularization parameter. Extensive experiments demonstrate that the proposed approach produces results superior to most methods in both visual image quality and quantitative measures.

关键词： Blind deconvolution Total variation Spatially adaptive parameter image restoration Medical image

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