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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81-90 订阅

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Descreening method of scanned halftone image based on wavelet

Descreening method of scanned halftone image based on wavele...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Yi, Yaohua Liu, Juhua Yu, Changhui Qin, Qlanqing Wuhan Univ Sch Printing & Packaging 129 Luoyu Rd Wuhan 430079 Peoples R China Wuhan Univ Sch Remote Sensing Informat Engn 2 Wuhan 430079 Peoples R China Wuhan Univ State Key Lab Informat Engn Surveying Mapping & Remote Sensing Wuhan 430079 Peoples R China

ISBN: (纸本)9780819469502

In the workflow of image reproduction, the halftone image is usually used as scanned original image. The moire patterns are a result of intervention during the process of scanning. This paper provides a descreening method of scanned halftone image based on wavelet according to the cause and the character of moire patterns. Experiment result shows that this descreening method can remove the moire patterns effectively and at the same time hold the definition and entropy of the scanned halftone image.

关键词： descreening scanned halftone image wavelet

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Monopulse radar 3-d imaging and application in terminal guidance, radar

Monopulse radar 3-d imaging and application in terminal guid...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Xu, Hui Qin, Guodong Zhang, Lina Xidian Univ Inst Elect Engn Xian 710071 Peoples R China

ISBN: (纸本)9780819469502

Monopulse radar 3-D imaging integrates ISAR, monopulse angle measurement and 3-D imaging processing to obtain the 3-D image which can reflect the real size of a target, which means any two of the three measurement parameters, namely azimuth difference beam, elevation difference beam and radial range, can be used to form 3-D image of 3-D object. The basic principles of Monopulse radar 3-D imaging are briefly introduced, the effect of target carriage changes(including yaw, pitch, roll and movement of target itself) on 3-D imaging and 3-D moving compensation based on the chirp rate mu and Doppler frequency f(d) are analyzed, and the application of monopulse radar 3-D imaging to terminal guidance radars is forecasted. The computer simulation results show that monopulse radar 3-D imaging has apparent advantages in distinguishing a target from overside interference and precise assault on vital part of a target, and has great importance in terminal guidance radars.

关键词： monopulse 3-D imaging target carriage change terminal guidance radar

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Linear object extraction from high-resolution image based on MRF and Bayesian

Linear object extraction from high-resolution image based on...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Yu, Changhui Meng, Lingkui Yi, Yaohua Yang, Zhigao Wuhan Univ Sch Remote Sensing Informat Engn 129 Luoyu Rd Wuhan 430079 Peoples R China Wuhan Univ Sch Printing & Packaging Wuhan AH-430079 Peoples R China Wuhan Univ State Key Lab Informat Engn Surveying Mapping & Remote Sensing Wuhan AH-430079 Peoples R China

ISBN: (纸本)9780819469502

The commercialization of high resolution remote sensing image provides the image application more widely space. How to extract the interested important objects quickly and exactly from remote sensing image is always the research focus. After analyzed the characteristics of road in high resolution image, the paper constructed the road extraction model based on MRF and Bayesian. And finally the validity of the method was confirmed by an example.

关键词： high resolution remote sensing image bayesian markov random field

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Fingerprint segmentation based on local Fourier transform

Fingerprint segmentation based on local Fourier transform

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Fan, Dongjin Feng, Jufu Peking Univ Sch Elect Engn & Comp Sci Dept Machine Intelligence State Key Lab Machine Percept Beijing 100871 Peoples R China

ISBN: (纸本)9780819469502

The segmentation of fingerprint images plays an important role in fingerprint recognition. A new algorithm based on Local Fourier Transform (LFT) for the fingerprint segmentation is proposed in this paper. Firstly, we perform the Local Fourier Transform on image to get eight independent Local Fourier coefficients per pixel. Then, block features are extracted by calculating the 2(nd), 4(th), 6(th) order moments of the local Fourier coefficients of every pixel in the block. After that, a Fisher linear discriminant classifier is trained for the classification per block. Finally, mathematical morphology and region boundary smoothing is applied as postprocessing to obtain compact clusters and to reduce the number of classification errors. The experimental results on the databases of FVC2004 demonstrate the robustness and the efficiency of the proposed method.

关键词： image segmentation local Fourier transform linear classification

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Synthetic aperture radar automatic target recognition based on curvelet transform

Synthetic aperture radar automatic target recognition based ...

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mippr 2009 - automatic target recognition and image analysis: 6th International Symposium on multispectral image Processing and Pattern recognition

作者： Wang, Shuang Liu, Zhuo Jiao, Licheng He, Jun Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

A novel synthetic aperture radar (SAR) automatic target recognition (ATR) approach based on Curvelet Transform is proposed. However, the existing approaches can not extract the more effective feature. In this paper, our method is concentrated on a new effective representation of the moving and stationary target acquisition and recognition (MSTAR) database to obtain a more accurate target region and reduce feature dimension. Firstly, MSTAR database can be extracted feature through the optimal sparse representation by curvelets to obtain a clear target region. However, considering the loss of part of edges of image. We extract coarse feature, which is to compensate fine feature error brought by segmentation. The final features consisting of fine and coarse feature are classified by SVM with Gaussian radial basis function (RBF) kernel. The experiments show that our proposed algorithm can achieve a better correct classification rate. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： automatic target recognition

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Real time tracking by LOPF algorithm with mixture model

Real time tracking by LOPF algorithm with mixture model

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

作者： Meng, Bo Zhu, Ming Han, Guangliang Wu, Zhiguo Changchun Institute of Optics Fine Mechanics and Physics Chinese Acadamy of Sciences ChangChun 130033 China Graduate School Chinese Academy of Sciences Beijing 100039 China 16 Dongnanhu Road Changchun 130033 China

ISBN: (纸本)9780819469502

A new particle filter-the Local Optimum Particle Filter (LOPF) algorithm is presented for tracking object accurately and steadily in visual sequences in real time which is a challenge task in computer vision field. In order to using the particles efficiently, we first use Sobel algorithm to extract the profile of the object. Then, we employ a new Local Optimum algorithm to auto-initialize some certain number of particles from these edge points as centre of the particles. The main advantage we do this in stead of selecting particles randomly in conventional particle filter is that we can pay more attentions on these more important optimum candidates and reduce the unnecessary calculation on those negligible ones, in addition we can overcome the conventional degeneracy phenomenon in a way and decrease the computational costs. Otherwise, the threshold is a key factor that affecting the results very much. So here we adapt an adaptive threshold choosing method to get the optimal Sobel result. The dissimilarities between the target model and the target candidates are expressed by a metric derived from the Bhattacharyya coefficient. Here, we use both the counter cue to select the particles and the color cur to describe the targets as the mixture target model. The effectiveness of our scheme is demonstrated by real visual tracking experiments. Results from simulations and experiments with real video data show the improved performance of the proposed algorithm when compared with that of the standard particle filter. The superior performance is evident when the target encountering the occlusion in real video where the standard particle filter usually fails.

关键词： target tracking

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image denoising with window shrink wavelet coefficients by adaptive threshold - art. no. 678613

Image denoising with window shrink wavelet coefficients by a...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Zhao, Yifan Li, Jiuxian Xia, Liangzheng SE Univ Dept Automat Control Nanjing 210096 Peoples R China

ISBN: (纸本)9780819469502

We introduce an adaptive wavelet coefficients shrinkage method and apply it to image denoising. Donoho's denoising scheme which is based on thresholding the wavelet coefficients, eliminates too many wavelet coefficient without considering the image's local characteristics. In this paper we propose a new shrinkage method which can modify the magnitude of shrinkage by considering neighboring wavelet coefficients and variance of noise. So we can use more wavelet decomposition levels than other wavelet shrinkage methods to recover the noisy images. The proposed method outperforms the other methods given in literature, while its implementation and concept are both simple.

关键词： wavelet shrinkage image denoising adaptive threshold neighboring coefficients

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Transfer network learning based remote sensing target recognition

Transfer network learning based remote sensing target recogn...

引用

mippr 2009 - automatic target recognition and image analysis: 6th International Symposium on multispectral image Processing and Pattern recognition

作者： Gou, Shuiping Wang, Yuqin Jiao, Licheng Key Laboratory of Intelligent Perception and Image Understanding for the Ministry of Education Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

The target recognition accuracy of remote sensing images is not satisfied. The labels of images acquisition and recollecting are difficult and expensive. In order to solve the problem, we introduce transfer learning into Network Boosting algorithm (NB) and propose Transfer Network Learning algorithm (TNL), in which other out-date data are reused to instruct the remote sensing target recognition. TNL is suitable to improve the performance of remote sensing target recognition, in which instances transfer learning is adopted for domain adaptation. The experimental results on the MSTAR SAR data set and remote sensing data set including two-class planes show that the proposed algorithm has better performance and achieves different domains learning. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Learning algorithms

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Efficient and robust global motion estimation for n automatic target recognition

Efficient and robust global motion estimation for n automati...

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

作者： Ming, Jin Bin, Xue Dingming, Peng Department of Image Analysis Laboratory Southwest Automation Research Institute Mianyang Sichuan Province 621000 China

ISBN: (纸本)9780819469502

In the automatic target recognition with complex background, the method of detecting motion target using the global motion estimation (GME) in image sequences is often proposed. Due to the possible presences of differently moving foreground objects and other sources of distortions, improvement of robustness and preciseness of GME is very difficult. Therefore the method of GME based on the M-estimators' formulation with direct multi-resolution is proposed in our paper. The M-estimators' formulation is not only executed in gradient descent at each level of the pyramid, but also applied in initial translation estimation with minimal SSD at the coarsest level, which assures the convergence of the subsequent gradient descent algorithm. Comparative experiments are performed to validate the performance of the proposed algorithm. The effectiveness and improvements can be observed from the comparisons.

关键词： Motion estimation

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Color image segmentation by integrating texture measure into JSEG method

Color image segmentation by integrating texture measure into...

引用

5th International Symposium on multispectral image Processing and Pattern recognition

作者： Sheng, Qinghong Zhang, Jianqing Xiao, Hui Wuhan Univ Inst Remote Sensing & Informat Engn Wuhan 430079 Peoples R China

ISBN: (纸本)9780819469502

We present a new color image segmentation method that combined texture measures and the JSEG (J measure based JSEGmentation) algorithm. In particular, two major contributions are set forth in this paper. (1) The two measures defined in JSEG and the Laws texture energy is discussed respectively and then we find that the over-segmentation problem of JSEG could be attributed partly to the absence of color discontinuity in the J measure. (2) A new measure is proposed by integrating the Laws texture energy measures into the J measure, on which our segmentation method is based. The new segmentation method taking account of both textural homogeneity and color discontinuity in local regions can be used to detect proper edges at the boundaries of shadows and highlights. Performance improvement due to the proposed modification was demonstrated on a variety of real color images.

关键词： color image segmentation JSEG Laws texture energy homogeneity measure

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