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2010 17th IEEE International Conference on image processing, ICIP 2010

作者： Wang, Y.Q. Chen, W.F. Yu, T.L. Zhang, Y.T. Tianjin Key Lab. of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin 300191 China Key Lab. of Image Processing Southern Medical University Guangzhou 510515 China Dept. of Radiology General Hospital Tianjin Medical University Tianjin 300052 China

ISBN: (纸本)9781424479948

Active contours have been one of the most successful methods for image segmentation during the last two decades, but one of the shortcomings of being unable to converge to concavity is a handicap to its effectiveness. In order to address this issue, the gradient vector flow (GVF) was put forth. Although there have been a great number of works on GVF, the image structure has seldom been incorporated into GVF algorithm. In this work, the image structure characterized by the Hessian matrix is incorporated into the GVF algorithm by reformulating the smoothness constraint of GVF into matrix form. In this way, the associated diffusion PDEs are anisotropic and the modified GVF snake can converge to very long concavity and preserve weak edge simultaneously. Experiments and comparisons are presented to demonstrate the properties of the proposed strategies. © 2010 IEEE.

关键词： image segmentation

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Second ACM international workshop on multimedia in forensics, security and intelligence (MiFor 2010)

Second ACM international workshop on multimedia in forensics...

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作者： Battiato, Sebastiano Emmanuel, Sabu Ulges, Adrian Worring, Marcel Image Processing Lab. University of Catania Viale Andrea Doria 6 95125 Catania Italy School of Computer Engineering Nanyang Technological University 639 798 Singapore Singapore Trippstadter Str. 122 D-67663 Kaiserslautern Germany Intelligent Systems Lab. Amsterdam University of Amsterdam Science Park 107 1098 XG Amsterdam Netherlands

This paper introduces the context of the workshop and the associated papers.

ISBN: (纸本)9781605589336

This paper introduces the context of the workshop and the associated papers.

关键词： Computer vision

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Single channel speech separation with a frame-based pitch range estimation method in modulation frequency

2010 5th International Symposium on Telecommunications, IST ...

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2010 5th International Symposium on Telecommunications, IST 2010 2010年 609-613页

作者： Mahmoodzadeh, A. Abutalebi, H.R. Soltanian-Zadeh, H. Sheikhzadeh, H. Speech Proc. Research Lab. ECE Dept. Yazd University Iran Control and Intelligent Processing Center of Excellence University of Tehran Iran EE Dept. Amirkabir University of Technology Tehran Iran Idiap Research Institute Martigny Switzerland Image Analysis Lab. Henry Ford Health System Detroit United States

ISBN: (纸本)9781424481835

Computational Auditory Scene Analysis (CASA) has attracted a lot of interest in segregating speech from monaural mixtures. In this paper, we propose a new method for single channel speech separation with frame-based pitch range estimation in modulation frequency domain. This range is estimated in each frame of modulation spectrum of speech by analyzing onsets and offsets. In the proposed method, target speaker is separated from interfering speaker by filtering the mixture signal with a mask extracted from the modulation spectrogram of mixture signal. Systematic evaluation shows an acceptable level of separation comparing with classic methods. © 2010 IEEE.

关键词： Frequency estimation

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Determination of pitch range based on onset and offset analysis in modulation frequency domain

2010 5th International Symposium on Telecommunications, IST ...

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2010 5th International Symposium on Telecommunications, IST 2010 2010年 604-608页

作者： Mahmoodzadeh, A. Abutalebi, H.R. Soltanian-Zadeh, H. Sheikhzadeh, H. Speech Proc. Research Lab. ECE Dept. Yazd University Yazd Iran Control and Intelligent Processing Center of Excellence University of Tehran Tehran Iran EE Dept. Amirkabir University of Technology Tehran Iran Idiap Research Institute Martigny Switzerland Image Analysis Lab. Henry Ford Health System Detroit United States

ISBN: (纸本)9781424481835

Auditory scene in a natural environment contains multiple sources. Auditory scene analysis (ASA) is the process in which the auditory system segregates a scene into streams corresponding to different sources. The determination of range of pitch frequency is necessary for segmentation. We propose a system to determine the range of pitch frequency by analyzing onsets and offsets in modulation frequency domain. In the proposed system, first the modulation spectrum of speech is calculated and then, in each subband onsets and offsets will be detected. Thereafter, the segments are generated by matching corresponding onset and offset front. Finally, by choosing the desired segments, the rage of pitch frequency is determined. Systematic evaluation shows that the range of pitch frequency is estimated with good accuracy. © 2010 IEEE.

关键词： Frequency modulation

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A comparative study of radial basis function neural networks in dynamic clustering algorithm

A comparative study of radial basis function neural networks...

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MIPPR 2009 - Pattern recognition and Computer Vision: 6th International Symposium on Multispectral image processing and Pattern recognition

作者： Zhou, Peng Li, Dehua Wu, Hong Zeng, Jun Chen, Feng State Key Lab. for Image Processing and Intelligent Control Institute for Pattern Recognition and Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478078

This paper developed two learning procedure, respectively, based on the orthogonal least squares (OLS) method and the "Innovation- Contribution" criterion (ICc) proposed newly. The orthogonal use of the stepwise-regression algorithm of the ICc mages the model structure independent of the selected term sequence and reduces the cluster region further as compared with orthogonal least squares (OLS). as the Bayesian information criteria (BIC) method is incorporate into the clustering process of the ICc, except for the widths of Gaussian functions, it has no other parameter that need tuning ,but the user is required to specify the tolerance ρ, which is relevant to noises and will be difficult to implement in the real system, for the OLS algorithm. The two algorithms are employed to the Radial Basis Function Neural Networks (RBFNN) to compare its performance for different noise nonlinear dynamic systems. Experimental results show that they provide an efficient approximation to the required results for fitting models, but the clustering procedures of the ICc is substantially better solutions than does the OLS. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Radial basis function networks

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SAR image despeckling based on edge detection and nonsubsampled second generation bandelets

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Journal of Systems Engineering and Electronics 2009年第3期20卷 519-526页

作者： Zhang Wenge~(1,2),Liu Fang~(1,2),Jiao Licheng~(2,3)& Gao Xinbo~(2,3) 1.School of Computer Science and Technology,Xidian Univ.,Xi’an 710071,P.R.China 2.Key lab.of intelligent Perception and image Understanding of Ministry of Education of China,Xi’an 710071,P.R.China 3.Inst,of intelligent Information processing,Xidian Univ.,Xi’an 710071,P.R.China School of Computer Science and Technology Xidian Univ. Xi'an 710071 P. R. China Key Lab. of Intelligent Perception and Image Understanding of Ministry of Education of China Xi'an 710071 P. R. China Key Lab. of Intelligent Perception and Image Understanding of Ministry of Education of China Xi'an 710071 P. R. China Inst. of Intelligent Information Processing Xidian Univ. Xi'an 710071 P. R. China

To preserve the sharp features and details of the synthetic aperture radar （SAR） image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform （NSBT） domain is proposed. First, the Canny operator is utilized to detect and remove edges from the SAR image. Then the NSBT which has an optimal approximation to the edges of images and a hard thresholding rule are used to approximate the details while despeckling the edge-removed image. Finally, the removed edges are added to the reconstructed image. As the edges axe detected and protected, and the NSBT is used, the proposed algorithm reaches the state-of-the-art effect which realizes both despeckling and preserving edges and details simultaneously. Experimental results show that both the subjective visual effect and the mainly objective performance indexes of the proposed algorithm outperform that of both Bayesian wavelet shrinkage with edge detection and Bayesian least square-Gaussian scale mixture （BLS-GSM）.

关键词： computer image processing synthetic aperture radar speckle edge detection nonsubsampled second generation bandelet transform Canny operator threshold shrinkage.

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Bayesian nonlocal means filter for SAR image despeckling

Bayesian nonlocal means filter for SAR image despeckling

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2009 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2009

作者： Zhong, Hua Li, Yongwei Jiao, Licheng Key Lab. of Intelligent Perception and Image Understanding of the Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781424427314

The nonlocal (NL) means filter as a recent denoising approach has demonstrated its empirical merit for additive Gaussian noise. In this paper, a novel Bayesian nonlocal (BNL) means filter is derived, which is adapted to the multiplicative speckle noise. The new filter is better parameterized using the Bayesian framework, in which a new statistical distance is introduced to measure the similarity of speckled patches. The proposed method is validated on real synthetic aperture radar (SAR) images through comparisons with other classical despeckling methods. ©2009 IEEE.

关键词： Synthetic aperture radar

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Change detection based on image segment and fusion in multitemporal SAR images

Change detection based on image segment and fusion in multit...

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2009 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2009

作者： Wang, Guiting Gu, Zhenquan Jiao, Licheng Fan, Yuanzhang Key Lab. of Intelligent Perception and Image Understanding of Theminisfry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781424427314

In this paper, a new change detection method based on image segmentation and fusion in multi-temporal SAR image is presented. The proposed fusion method exploits the conditional probability of difference image to two original images to fuse the segment results of two original SAR images. The new method can be divided into four steps: 1) the original SAR images are segmented into two classes using the proposed segmentation method based on canny edge match. 2) The two segmentation result images are fused with conditional probability rule and a fusion difference image considering spatial context is obtained. 3) The fusion image is thresholded with OTSU threshold, and the initial change detection result is obtained. 4) With subtraction operation and absolute operation between two segment results of original SAR images, a Boolean image with 0 and 1 value is obtained. Then the change detection result is composed of the regions in the Boolean image corresponding to the change regions in the initial change detection result. Experimental results obtained on simulate and real SAR images confirm the effectiveness of the proposed approach. ©2009 IEEE.

关键词： image fusion

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An automatic bridge detection technique for high resolution SAR images

An automatic bridge detection technique for high resolution ...

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2009 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2009

作者： Wang, Guiting Huang, Shan Jiao, Licheng Key Lab. of Intelligent Perception and Image Understanding of Theministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781424427314

In this paper, an approach for detecting bridges over water bodies from high resolution SAR images is presented. It consists of two steps: water extraction and bridge detection. A method based on porosity combined with an edge mending algorithm utilizing canny edges is used to extract water bodies firstly. By considering the ubiety of bridges and water bodies, the candidate bridge regions are detected. Then the candidate bridge regions are confirmed on the basis of the geometric characteristics of bridges. Finally bridges are detected in confirmed bridge regions according to geometric characteristics of bridges and water extraction result. The proposed approach has been tested with SAR images that have a spatial resolution of 1 m. The experimental results show that our method can detect bridges effectively. ©2009 IEEE.

关键词： Porosity

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A contourlet-based interpolation restoration method for super-resolution of SAR image

A contourlet-based interpolation restoration method for supe...

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2009 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2009

作者： Zhang, Xiaohua Cao, Kun Jiao, Licheng Key Lab. of Intelligent Perception and Image Understanding of the Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781424427314

As is well known that the quality of a digital image is affected by many factors, such as the distance between the acquisition system and the object, the acquisition environment conditions, and the resolution of the image sensors employed, and so on. So how to obtain high quality images has become a difficult task in practical applications. image super-resolution reconstruction (SRR) is a signal processing approach which can produces a high-resolution (HR) image from observed multiple low-resolution (LR) images. The purpose of this study is to evaluate the potential application of SR techniques to synthetic aperture radar (SAR). In this paper, a LR image is used to extract high frequency information and reconstruct a high resolution image by an interpolation- restoration method based on contourlet transform to solve the problem of SRR. Experimental results show that the method has the superior performance in subjective visual quality. ©2009 IEEE.

关键词： image reconstruction

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