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Classification based nonlocal means despeckling for SAR image

Classification based nonlocal means despeckling for SAR imag...

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MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Zhong, Hua Xu, Jingjing Jiao, Licheng Institution of Intelligent Information Processing Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

The nonlocal (NL) means filter as a recent denoising approach has demonstrated its empirical merit for additive Gaussian noise. In this paper, a new nonlocal means despeckling method for synthetic aperture radar (SAR) image is proposed, which is adapted to the multiplicative model of speckle noise. The proposed method still uses Euclidean distance based similarity measure but adopting a strategy of pixel classification, which can effectively reduce the influence of the multiplicative speckle model and improve the effectiveness in searching of similar patches, thus contributes to the final results. By this strategy, image pixels are first classified into different classes such as point, line, edge, etc., and then different smooth parameters of nonlocal means filter are used according to the class information. In addition, a searching method for rotation-invariant similar patches is designed through the use of directional information. We validate the proposed method on real synthetic aperture radar (SAR) images and confirm the excellent despeckling performance through comparisons with other classical despeckling methods, such the Enhanced Lee filter, Enhanced Gamma MAP filter, wavelet thresholding, as well as original NL mean filter. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： image classification

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Transfer learning for kernel matching pursuit on computer-aided diagnoses

Transfer learning for kernel matching pursuit on computer-ai...

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

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

ISBN: (纸本)9780819478085

It is commonplace for the lack of labeled data in novel domains on medical image computer-aided diagnosis but there have been some labeled data or prior knowledge in old correlative domains. In this paper, instance-transfer approach is introduced into medical image processing. And then we present a novel transfer learning model based on kernel matching pursuit called TLKMP, which extends KMP (kernel matching pursuit learning machine, Vincent & Bengio, 2002). TLKMP uses the Greedy Approximation Residue to transfer instances into target domains which have little labeled set different distributions from the source domains. So, valuable instances in resource domains are reused to construct high quality classification model for the unlabeled set of the target domains. The experiment is performed datasets on Gastric Cancer of Lymph Node database which comes from some a hospital. The results show that the proposed algorithm has better classification performance compared with traditional KMP methods, and it improves diagnosis accuracy rate of medical images effectively the same as the algorithm need lest labeled data for training a good classification model. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Computer aided diagnosis

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Fuzzy PID control of a wearable rehabilitation robotic hand driven by pneumatic muscles

Fuzzy PID control of a wearable rehabilitation robotic hand ...

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20th Anniversary MHS 2009 and Micro-Nano Global COE - 2009 International Symposium on Micro-NanoMechatronics and Human Science

作者： Wu, Jun Huang, Jian Wang, Yongji Xing, Kexin Xu, Qi Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology 430074 Wuhan China

ISBN: (纸本)9781424450954

Intensive task-oriented repetitive physical therapies need be provided by individualized interaction between the patients and the rehabilitation specialists to improve hand motor performance for those survived from stoke and traumatic brain injury. The goal of this research is to develop a novel wearable device for robotic assisted hand repetitive therapy. We designed a pneumatic muscle (PM) driven therapeutic device that is wearable and provides assistive forces required for grasping and finger extension. The robot has two distinct degrees of freedom at the thumb and all other fingers. The embedded sensors can feedback position and force information for robot control and quantitative evaluation of task performance. It is potential of providing supplemental at-home therapy in addition to in the clinic treatment. To realize the trajectory tracking control, a fuzzy PID controller is designed for the proposed device. The experimental results show angle tracking control of the robotic hand using the fuzzy PID controller has better performance than that using a conventional PID controller. ©2009 IEEE.

关键词： Wearable technology

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ICSA based projection pursuit clustering with LDA index and its application in SAR image segmentation

ICSA based projection pursuit clustering with LDA index and ...

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

作者： Gou, Shuiping Feng, Jing Jiao, Licheng He, Xiao 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)9781424427314

The performance of the traditional clustering algorithm is not always satisfied with the high-dimensional datasets, which make clustering method limited in many application. To solve this problem, Projection Pursuit with LDA index based on Immune Clonal Selection Algorithm is proposed in this paper. Projection pursuit strategy can maintain consistent Euclidean distances between points in the low-dimensional embeddings where the ICSA is used to search optimal projection direction. In the proposed algorithm, k-mean clustering algorithm is used to partition the reduced data and give labels to LDA index, and iterations have been done for several times can converge quickly to obtain a clustering result. The experimental results on UCI data show that the present method has better clustering accuracy compared with traditional linear dimension reduction method for principle component analysis (PCA). And the experiments on SAR image segmentation also have a good performance. ©2009 IEEE.

关键词： Clustering algorithms

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A novel interference cancellation approach for interleaved OFDMA uplink system

A novel interference cancellation approach for interleaved O...

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作者： Miao, Ruiqin Sun, Jun Gui, Lin Xiong, Jian Institute of Image Communication and Information Processing Department of Electronic Engineering Shanghai Jiao Tong University Shanghai 200240 China Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiao Tong University Shanghai 200240 China

In this paper, the issue of carrier frequency offset (CFO) compensation in interleaved orthogonal frequency division multiple access (OFDMA) uplink system is investigated. To mitigate the effect of multiple access interference (MAI) caused by CFOs of different users, a new parallel interference cancellation (PIC) compensation algorithm is proposed. This scheme uses minimum mean square error (MMSE) criterion to obtain the estimation of interference users, then circular convolutions [6] are employed to restore MAI and compensate CFO. To tackle the complexity problem of circular convolutions, an efficient MAI restoration and cancellation method is developed. Simulations illustrate the good performance and low computational complexity of the proposed algorithm. © 2009 The Institute of Electronics, Information and communication Engineers.

关键词： Mean square error

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SAR image segmentation based on immune greedy spectral clustering

SAR image segmentation based on immune greedy spectral clust...

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

作者： Gou, S.P. Zhang, J. Jiao, L.C. 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)9781424427314

In this paper we propose a novel spectral clustering algorithm called Immune Greedy Spectral Clustering Algorithm, which introduces immune clone selection algorithm instead of greedy selection to choose a subset before greedy spectral embedding without any prior experiment knowledge. As we know, Nyström algorithm is a random selecting method which depends so much on the selecting result so that the clustering result fluctuates obviously. Greedy spectral clustering algorithm acquires a subset called dictionary by greedy selection algorithm so that the result could be more stable and better. However, to choose an appropriate input tolerance, we need prior experiment knowledge about the relationship between tolerance and select number. Moreover, since the criterion used for greedy selection is the distance in feature space between a candidate example and its projection on the subspace spanned by selected examples, we need to compute every example point one by one to get the error of using the selected examples to approximate the candidate example and then decide whether to choose it. So the time expense increases inevitable. Considering all above, we present a new method called Immune Greedy Spectral Clustering Algorithm. The experimental results show that Immune Greedy Spectral Clustering Algorithm need no prior experiment knowledge and could save time compared with greedy spectral clustering while getting a better accuracy rate compared with Nyström algorithm. ©2009 IEEE.

关键词： Cloning

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Transfer network learning based remote sensing target recognition

Transfer network learning based remote sensing target recogn...

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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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Motion vector recovery for H.264 based on mean shift

Motion vector recovery for H.264 based on mean shift

引用

Asia-Pacific Conference on communications

作者： Xuefeng Zhan Xiuchang Zhu Image Processing and Image Communication Laboratory Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781424447848

In this paper, we describe a novel motion vector (MV) recovery method for H.264 which is based on mean shift procedure. In H.264, macroblock (MB) can be divided into several 4×4 blocks. Generally, MVs of these blocks in local region are very similar. To conceal the lost MB temporally, we consider the MV recovery of the lost MB as smooth operation in the neighboring area. The mean shift procedure is applied here to estimate MVs of lost blocks. Experimental results demonstrate their better performance.

关键词： Kernel Interpolation Error correction Partitioning algorithms Motion estimation Video compression Clustering algorithms image processing image communication Lagrangian functions

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Fuzzy Reasoning Based Temporal Error Concealment

Fuzzy Reasoning Based Temporal Error Concealment

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Xuefeng Zhan Xiuchang Zhu Image Processing and Image Communication Laboratory Nanjing University of Posts and Telecommunications Nanjing China

A novel temporal error concealment based on fuzzy reasoning is proposed in this paper. On temporal error concealment, motion vector (MV) of the lost block can be selected from candidate MVs. Generally, side match distortion (SMD) which reflects the continuity across the boundary and sum of absolute difference (SAD) which shows the degree of similarity of matching area are two widely used criterions to make the decision. Each criterion describes the status partly. Combining these two measures, a refined measure based on fuzzy reasoning is calculated to balance the effects of SMD and SAD. According to the experimental results, our method can perform better than the others.

关键词： Fuzzy reasoning Distortion measurement Interpolation Decoding Motion estimation Fuzzy systems image processing image communication image coding Motion compensation

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image complexity adaptive intra-frame rate control algorithm for H.264/AVC

Image complexity adaptive intra-frame rate control algorithm...

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International Conference on Wireless communications and Signal processing (WCSP)

作者： Ziguan Cui Xiuchang Zhu Image Processing and Image Communication Laboratory Nanjing University of Posts and Telecommunications Nanjing China

Aiming at the bad effect of intra-frame rate control (RC) of H.264, this paper proposed an image complexity adaptive intra-frame RC algorithm. First, in order to acquire intra-frame coding complexity more accurately, our algorithm analyzes intraframe by Sobel operator and establishes edge direction histogram for each 4×4 block, then gets the most probable intra prediction mode and corresponding reconstructed blocks, finally obtains the residual picture which is close to the actual coding residual. The mean absolute value of residual picture was used to represent the intra-frame coding complexity, combined with our empirical rate-quantization (R-Q) model and target bits allocation method from exhaustive experiments, and the intra QP was determined accurately. Extensive experimental results show that our algorithm not only obtains more accurate intra-frame output bitrate, more consistent subjective quality and more steady PSNR fluctuation compared with existing algorithm, but also prevents buffer overflow and frame skip effectively.

关键词： Programmable control Adaptive control Automatic voltage control Bit rate Radio control Algorithm design and analysis Histograms image reconstruction Quadratic programming PSNR

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