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Encoding Methods of Spectral Vector in Hyperspectral Romote Sensing image

Journal of Shanghai University(English Edition) 2005年第1期9卷 52-57页

作者：杜培军方涛唐宏施鹏飞 Department of Remote Sensing and Geographical Information Science China University of Mining and Technology Xuzhou 221008 P.R. China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200030 P.R. China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200030 P.R. China

Taking into account the demands of hyperspectral remote sensing(RS) image retrieval and processing, some encoding methods of spectral vector including direct encoding, feature-based encoding and tree-based encoding methods are proposed and compared. In direct encoding, based on the analysis of binary encoding and quad-value encoding, decimal encoding is proposed. It is proved that quad-value encoding and decimal encoding are suitable to fast processing and retrieval. In absorption feature-based encoding method, five common metrics are compared. Because locations of reflection/absorption features are sensitive to noise, this method is not very effective in retrieval. In tree-based encoding methods, bitree, quadtree, octree and hextree are proposed and discussed. It is proved that 2-level octree and 2-level hextree are more effective than bitree and quadtree. Finally, quad-value encoding, decimal encoding, 2-level octree and 2-level hextree are proposed in spectral vectors encoding, similarity measure and hyperspectral RS image retrieval.

关键词： hyperspectral remote sensing spectral vector encoding similarity measure spectral angle.

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Multiple objects segmentation based on maximum-likelihood estimation and optimum entropy-distribution (MLE-OED)

Multiple objects segmentation based on maximum-likelihood es...

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International Conference on pattern recognition

作者： Xie Jun H.T. Tsui Xia Deshen Image Processing and Computer Vision Laboratory Department of Electronic Engineering Chinese University of Hong Kong Hong Kong China Pattern Recognition Laboratory Department of Computer Science Nanjing University of Science and Technology China

ISBN: (纸本)076951695X

A new method based on MLE-OED is proposed for unsupervised image segmentation of multiple objects which have fuzzy edges. It adjusts the parameters of a mixture of Gaussian distributions via minimizing a new loss function proposed to implement image segmentation based on the image's local spatial information and global intensity distribution properties. The loss function consists of two terms: a local content fitting term, which optimizes the entropy distribution, and a global statistical fitting term, which maximizes the likelihood of the parameters for the given data. The proposed segmentation method was validated by simulated and real examples. The performance in the experiments is better than those of two popular methods.

关键词： Object segmentation Maximum likelihood estimation image segmentation Layout Uncertainty image edge detection Shape measurement image processing pattern recognition Gaussian distribution

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Double-Row Cascade Labeling Algorithm for Hyper-Scale Issue

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Procedia Engineering 2011年 15卷 4047-4051页

作者： Yebin Fan Hualong Zhao Department of Computer Science Huazhong University of Science and Technology National Key Laboratory of Science and Technology on Multi-Spectral Information Processing Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology

An efficient algorithm is presented to label the connected components in the case that the primary memory is smaller than the image data. Our algorithm uses only the memory of two image rows to label the huge image or any image larger than the available memory. The search path compression is a applied for improving the performance further. An extensive comparison with the state-of-art algorithms is proposed, both on random and real datasets. Our algorithm shows an impressive speedup, while the auxiliary memory is not required at all comparing with all competitors.

关键词： Connected components labeling page fault hyper-scalar union-find

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Transmit power allocation for an extended V-BLAST system

Transmit power allocation for an extended V-BLAST system

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Seung Hoon Nam Kwang Bok Lee Pattern Recognition and Image Processing Laboratory Samsung Advanced Institute of Science and Technology Suwon South Korea School of Electrical Engineering and Computer Science Seoul National University Seoul South Korea

ISBN: (纸本)0780375890

Vertical Bell Laboratories Layered Space-Time (V-BLAST) is a promising system that realizes the enormous capacity of multiple-input multiple-output (MIMO) communications. We present an extension of V-BLAST, and propose an effective transmit power allocation scheme for the extended system. The proposed transmit power allocation scheme minimizes the bit error rate (BER) averaged over all detection stages, and requires small feedback overhead from the receiver to the transmitter. Simulation results show that the extended V-BLAST system with the proposed transmit power allocation scheme provides a significant reduction in the BER compared to the conventional V-BLAST system. When the minimum mean square error (MMSE) nulling is adopted, the extended V-BLAST system is found to achieve the BER performance comparable to that of the maximum likelihood (ML) detection for the conventional V-BLAST architecture.

关键词： Bit error rate MIMO Feedback Transmitters Maximum likelihood detection Transmitting antennas Space technology computer science Mean square error methods Information theory

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Robust segmentation of freight containers in train monitoring videos

Robust segmentation of freight containers in train monitorin...

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IEEE Workshop on Applications of computer Vision (WACV)

作者： Qing-Jie Kong Avinash Kumar Narendra Ahuja Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Urbana IL USA

This paper is about a vision-based system that automatically monitors intermodal freight trains for the quality of how the loads (containers) are placed along the train. An accurate and robust algorithm to segment the foreground of containers in videos of the moving train is indispensable for this purpose. Given a video of a moving train consisting of containers of different types, this paper presents a method exploiting the information in both frequency and spatial domains to segment these containers. This method can accurately segment all types of containers under a variety of background conditions, e.g illumination variations and moving clouds, in the train videos shot by a fixed camera. The accuracy and robustness of the proposed method are substantiated through a large number of experiments on real data of train videos.

关键词： Robustness Freight containers Monitoring Videos image segmentation Rails Loading Clouds Cameras Lighting

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Scatter correction algorithm without extra exposure for dual-energy digital mammography

Scatter correction algorithm without extra exposure for dual...

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Medical Imaging 2009: Physics of Medical Imaging

作者： Xi, Chen Xuanqin, Mou Hao, Yan Hengyong, Yu Lei, Zhang Institute of Image Processing and Pattern Recognition Xi'an Jiaotong University Xi'an Shaanxi 710049 China Biomedical Imaging Division School of Biomedical Engineering and Science Virginia Tech. Blacksburg VA 240601 United States Department of Computing Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong Hong Kong

ISBN: (纸本)9780819475091

X-ray scatter leads to erroneous calculations of dual-energy digital mammography (DEDM). The existing methods for scatter correction in DEDM are using anti-scatter grids or the pinhole-array interpolation method which is complicated and impractical. In this paper, a scatter correction algorithm for DEDM is developed based on the knowledge that scatter radiation in mammograms varies slowly and most pixels in mammograms are non-microcalcification pixels. The proposed algorithm only uses the information of low-energy (LE) and high-energy (HE) images. And it doesn't need anti-scatter grids, lead sheet and extra exposures. Our results show that the proposed scatter correction algorithm is effective. When using the simple least-squares fit and linear interpolation, the scatter to primary ratio (SPR) can be decreased from ~33.4% to ~2.8% for LE image and from ~26.2% to ~0.8% for HE image. Applying scatter correction to LE and HE images, the resultant background signal in the DE (dual-energy) calcification image an be reduced significantly. ©2009 SPIE.

关键词： Pixels

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Analysis of appearance features for human matching between different fields of view

Analysis of appearance features for human matching between d...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Xiaowei Lv Qing-Jie Kong Fei Weng Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Beckman Institute Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Urbana IL USA

Human matching between different fields of view is a difficult problem in intelligent video surveillance; whereas fusing multiple features has become a strong tool to solve it. In order to guide the fusion scheme, it is necessary to evaluate the matching performance of these features. In this paper, four typical features are chosen for the evaluation. They are the color histogram, UV chromaticity, major color spectrum histogram, and scale-invariant features (SIFT). Quantities of video data are collected to test their general accuracy, robustness, and real-time applicability. The robustness is measured under the conditions of illumination changes, Gaussian and salt noises,foreground errors, resolution changes, and camera angle differences. The experimental results show that the four features bear distinctive performances under the different conditions, which will provide important references for the feature fusion methods.

关键词： Humans Colored noise Histograms Noise robustness Video surveillance Testing Noise measurement Lighting Gaussian noise Cameras

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SliceProp: A Slice-Wise Bidirectional Propagation Model for Interactive 3D Medical image Segmentation 1

SliceProp: A Slice-Wise Bidirectional Propagation Model for ...

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1st IEEE International Conference on Medical Artificial Intelligence, MedAI 2023

作者： Xu, Xin Lu, Wenjing Lei, Jiahao Qiu, Peng Shen, Hong-Bin Yang, Yang Shanghai Jiao Tong University Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai200240 China Shanghai Ninth People's Hospital Shanghai Jiao Tong University School of Medicine Department of Vascular Surgery China Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (纸本)9798350358780

Interactive medical image segmentation methods have become increasingly popular in recent years. These methods combine manual labeling and automatic segmentation, reducing the workload of annotation while maintaining high accuracy. However, most current interactive segmentation frameworks are limited to 2D image data, and are not suitable for 3D image data due to the large size and high complexity of 3D data, as well as the challenges posed by information asymmetry and sparse annotation. In this paper, we propose SliceProp, an interactive segmentation framework that implements slice-wise Label Bidirectional Propagation (LBP) for 3D medical image segmentation. SliceProp extends the interactive 2D image segmentation algorithm to 3D image segmentation, and can handle 3D data with large size and high complexity. Moreover, equipped with a Backtracking Feedback Check (BFC) module, SliceProp effectively addresses the issues of information asymmetry and spatial sparse annotation in 3D medical image segmentation. Additionally, we adopt an uncertainty-based criterion to pri-oritize the slices to be refined interactively, which enhances the efficiency of the interaction process by enabling the model to focus on the regions with the most unreliable predictions. SliceProp is evaluated on two datasets and achieves promising results compared to state-of-the-art methods. © 2023 IEEE.

关键词： Medical imaging

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Generalized stochastic tube model: tracking 3D blood vessels in MR images

Generalized stochastic tube model: tracking 3D blood vessels...

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International Conference on pattern recognition

作者： Qian Huang G.C. Stockman Almaden Research Center San Jose CA USA Pattern Recognition and Image Processing Laboratory Department of Computer Science Michigan State University East Lansing MI USA

This paper addresses the issue of tracking tubular objects, particularly blood vessels from MR images. A model-based approach is adopted. The generalized stochastic tube (GST) model is developed which is an extension of our previously proposed (1993) generalized tube (GT) model. Transitions among adjacent tubes are explicitly parameterized. Integrated with a bivariate Gaussian density function adopted to model the blood flow within cross sections, the GST model is applied to tracking blood vessels in MRA volumetric data. Experimental results on both synthetic data with different degrees of Gaussian noise and real MRA data demonstrated that simultaneously utilizing both models yields robust performance under noisy conditions.

关键词： Stochastic processes Blood vessels Biomedical imaging Shape Blood flow Gaussian noise image recognition Solid modeling pattern recognition Density functional theory

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Video Compression Artifacts Removal With Spatial-Temporal Attention-Guided Enhancement

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IEEE Transactions on Multimedia 2024年 26卷 5657-5669页

作者： Jiang, Nanfeng Chen, Weiling Lin, Jielian Zhao, Tiesong Lin, Chia-Wen Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information Fuzhou University Fuzhou350108 China Fujian Key Laboratory of Pattern Recognition and Image Understanding Xiamen University of Technology Xiamen361024 China Fujian Science and Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou350116 China Department of Electrical Engineering National Tsing Hua University Hsinchu30013 Taiwan Institute of Communications Engineering National Tsing Hua University Hsinchu30013 Taiwan

Recently, many compression algorithms are applied to decrease the cost of video storage and transmission. This will introduce undesirable artifacts, which severely degrade visual quality. Therefore, Video Compression Artifacts Removal (VCAR) aims at reconstructing a high-quality video from its corrupted version of compression. Generally, this task is considered as a vision-related instead of media-related problem. In vision-related research, the visual quality has been significantly improved while the computational complexity and bitrate issues are less considered. In this work, we review the performance constraints of video coding and transfer to evaluate the VCAR outputs. Based on the analyses, we propose a Spatial-Temporal Attention-Guided Enhancement Network (STAGE-Net). First, we employ dynamic filter processing, instead of conventional optical flow method, to reduce the computational cost of VCAR. Second, we introduce self-attention mechanism to design Sequential Residual Attention Blocks (SRABs) to improve visual quality of enhanced video frames with bitrate constraints. Both quantitative and qualitative experimental results have demonstrated the superiority of our proposed method, which achieves high visual qualities and low computational costs. © 2023 IEEE.

关键词： Computational complexity

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