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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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Partical swarm optimization based unequal loss protection of embedded video streams

Partical swarm optimization based unequal loss protection of...

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International Conference on Communication Technology (ICCT)

作者： Jiajing Hu Dong Hu The key Laboratory of image processing and image communications of Jiangsu Province Nanjing University of Posts and Telecommunications Nanjing China

This paper presents a new scheme for optimal packetization of scalable multimedia data over lossy network. By assigning an unequal amount of forward error correction (FEC) bits to each segment of transmission packets, the proposed algorithm protects a progressive bitstream generated by a three-dimensional set partitioning in hierarchical trees (3-D SPIHT) algorithm. The partical swarm optimization (PSO) algorithm is used to reasonably allocate bits between source coding and channel coding across packets. Experimental results show that the proposed algorithm provides close to optimal average peak signal-to-noise ratio performance and that its' running time is significantly lower than that of previously known solution.

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Replaying Styles for Continual Semantic Segmentation Across Domains 7th

Replaying Styles for Continual Semantic Segmentation Across...

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7th Asian Conference on Pattern Recognition, ACPR 2023

作者： Deng, Yao Xiang, Xiang Key Lab of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9783031476365

In the context of Domain Incremental Learning for Semantic Segmentation, catastrophic forgetting is a significant issue when a model learns new geographical domains. While replay-based approaches have been commonly used to mitigate this problem by allowing the model to review past knowledge, they require additional storage space for old data, which may not be feasible in real-world applications. To address this limitation, we propose a style replay method that leverages the characteristics of low-level representations in CNN to require only one style feature for each domain, leading to a significant reduction in storage overhead. By fusing the style features of past domains with the semantic features of current data, our method enables style transfer for new domain data, thereby improving the model’s generalization ability to the domain. Through extensive experimental evaluations on various autonomous driving datasets, we demonstrate the efficacy of our proposed method in addressing the challenges of continual semantic segmentation under both label and domain shift, outperforming the previous state-of-the-art methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Semantic Segmentation

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Small target detection using an optimization-based filter 40

Small target detection using an optimization-based filter

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40th IEEE International Conference on Acoustics, Speech, and Signal processing, ICASSP 2015

作者： Xie, Kai Fu, Keren Zhou, Tao Yang, Jie Wu, Qiang He, Xiangjian Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China School of Computing and Communications University of Technology Sydney Australia

ISBN: (纸本)9781467369978

Small target detection is a critical problem in the Infrared Search And Track (IRST) system. Although it has been studied for years, there are some challenges remained, e.g. cloud edges and horizontal lines are likely to cause false alarms. This paper proposes a novel method using an optimization-based filter to detect infrared small target in heavy clutter. First, we design a certain pixel area as active area. Second, a weighted quadratic cost function is performed in the active area. Finally, a filter based on statistics of active area is derived from the cost function. Our method could preserve heterogeneous area, meanwhile, remove target region. Experimental results show our method achieves satisfied performance in heavy clutter. © 2015 IEEE.

关键词： active area area statistics heavy clutter optimization-based filter small target detection

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An improved speech enhancement method based on teager energy operator and perceptual wavelet packet decomposition

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Journal of Multimedia 2011年第3期6卷 308-315页

作者： Zhao, Huan Peng, Xiujuan Hu, Lian Wang, Gangjin Yu, Fei Xu, Chen School of Information Science and Engineering Hunan University Changsha China Jiangsu Provincial Key Lab of Image Processing and Image Communications Nanjing University of Posts and Telecommunications Nanjing China

According to the distribution characteristic of noise and clean speech signal in the frequency domain, a new speech enhancement method based on teager energy operator (TEO) and perceptual wavelet packet decomposition (PWPD) is proposed. Firstly, a modified Mask construction method is made to protect the acoustic cues at the low frequencies. Then a level-dependent parameter is introduced to further adjust the thresholds in light of the noise distribution feature. At last the sub-bands which have very little influence are set directly 0 to improve the signal-to-noise ratio (SNR) and reduce the computation load. Simulation results show that, under different kinds of noise environments, this new method not only enhances the signal-to-noise ratio (SNR) and perceptual evaluation of speech quality (PESQ), but also reduces the computation load, which is very advantageous for real-time realizing. © 2011 ACADEMY PUBLISHER.

关键词： Signal to noise ratio

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Network flow based collective behavior analysis

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2013 International Workshop on Behavior and Social Informatics and Computing, BSIC 2013

作者： Hu, Yuting Xie, Rong Zhang, Wenjun Institute of Image Communication and Network Engineering Shanghai Key Lab. of Digital Media Processing and Transmission Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9783319040479

With the large-scale activities increasing gradually, the intelligent video surveillance system becomes more and more popular and important. The trajectory identification and behavior analysis are very important techniques for the intelligent video surveillance system. This paper focuses on the trajectory identification and behavior analysis framework for video surveillance system. The framework is implemented on footbridge video and queuing video of Shanghai World Expo 2010 video surveillance system. The experimental results show the efficiency of our proposed framework. © Springer International Publishing Switzerland 2013.

关键词： Integer programming

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Partial differential equation model method based on image feature for denoising

Partial differential equation model method based on image fe...

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International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Zhang, Xiaohua Wang, Ran Jiao, L.C. 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)9781424494040

For the special different nature images, we could hardly find particularly desirable approach, and there always exist Gibbs-type artifacts in the results of most methods. A novel Partial Differential Equation (PDE) model is proposed based on image feature for images denoising. The PDE model is adaptive within each region according to the details of the image feature to adjust the size of the diffusion coefficient. So it can be disposed the high gradient noise at the same time better to retain the edge information. We also analyze the performance of the PDE model method. Numerical results show that our algorithm competes favorably with state of the-art TV projection methods to eliminate noise and reduce Gibbs-type artifacts. ©2011 IEEE.

关键词： image denoising

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Unsupervised image segmentation based on nonsubsampled contourlet hidden markov trees model

Unsupervised image segmentation based on nonsubsampled conto...

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

作者： Xin, Fangfang Jiao, LiCheng Wan, Honglin Key Lab. 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)9781424427314

Based on the shift invariance and multidirectional expansion properties of Nonsubsampled Contourlet Transform, a new image segmentation combining hidden Markov trees model with Bayesian approaches is proposed here. The training blocks can be got in pre-segmentation by using histogram approximation. To integrated use the information of different scales, we use the contextual model to segment raw segmentations and fuse them to get the final image. We compared our result with Wavelet domain HMTseg method and Contourlet domain HMTseg method, the result shows that our method has better performance in edges but lower missed classed probability. The simulation results of synthetic mosaic image, aerial image and SAR image are showed to prove the generalization of this method. ©2009 IEEE.

关键词： image segmentation

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An improving MFCC features extraction based on FastICA algorithm plus RASTA filtering

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Journal of Computers 2011年第7期6卷 1477-1484页

作者： Zhao, Huan Hu, Lian Peng, Xiujuan Wang, Gangjin Yu, Fei Xu, Cheng School of Information Science and Engineering Hunan University Changsha China Jiangsu Provincial Key Lab of Image Processing and Image Communications Nanjing University of Posts and Telecommunications Nanjing China

FastICA is a kind of independent component analysis (ICA), which is robust and high performance algorithm, it can strongly remove signal correlation and ensure each signal to be independence. Through perceptual test, improving that RASTA is an idea which can denoise effectively. First, we remove signal correlation through FastICA algorithm, then we use RASTA filter to filtering the ceptral coefficients. Finally, we reduce dimension of the cepstral coefficients by the variances of cepstral coefficients in different dimension and obtain our features. By the HTK3.3, the speech feature extraction which was presented in this paper show the better robust in recognition experiment. © 2011 ACADEMY PUBLISHER.

关键词： Feature extraction

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