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

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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Integer Haar wavelet for romote sensing image compression 6

Integer Haar wavelet for romote sensing image compression

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6th International Conference on Signal processing, ICSP 2002

作者： Zhenhua, Wang Hongbo, Xu Yan, Tian Jinwen, Tian Jian, Liu State Key Lab. for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)0780374886

With the development of remote sensing technique, onboard data compression has become an urgent need and a lot of study has been directed toward the development of efficient techniques. In this paper, the construction approach of integer Haar is discussed briefly, and a'simple image compression scheme based on integer Haar Wavelet Transform and block DPCM is proposed. The scheme can be easily designed for data processing in real-time system of remote sensing with parellel algorithm. Simulation experimental results demonstrate that the proposed approach is a efficient image compression method. © 2002 IEEE.

关键词： image compression

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Underwater Perception and Autonomous Operation for Underwater Vehicle-Manipulator Systems: Methodology and Experiment

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IEEE/ASME Transactions on Mechatronics 2025年

作者： Jiang, Chaicheng Xiong, Xinyang Xiang, Xianbo Zeng, Zhigang Zhang, Fumin Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan 430074 China Huazhong University of Science and Technology School of Naval Architecture and Ocean Engineering Wuhan 430074 China Huazhong University of Science and Technology School of Naval Architecture and Ocean Engineering School of Artificial Intelligence and Automation State Key Lab of Intelligent Manufacturing Equipment and Technology Wuhan 430074 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control The Education Ministry of China Wuhan 430074 China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Clear Water Bay Hong Kong Hong Kong

Camera-equipped underwater vehicle-manipulator systems (UVMS) can achieve autonomous underwater operations through visual servoing. However, current methods excessively rely on auxiliary means for target's visual information and do not sufficiently consider the target's pose when designing visual servoing schemes. As a result, UVMS can only perform dynamic positioning or grasp simple-shaped targets like sea urchins. In this article, we are devoted to making the UVMS autonomously complete more complex underwater operations, such as valve switching and pipe handling. First, an underwater target perception system is proposed to address the issue of discontinuous target position estimation caused by various interferences. Second, a deep neural network-based grasping mechanism controller is proposed to enable the manipulator to grasp targets in various initial poses using the target image. Third, a decoupled visual servoing scheme is proposed for the motion control of the UVMS, and in collab.ration with a designed task supervisor to ensure that the UVMS can complete the underwater operation autonomously. To validate the effectiveness of the proposed methods, underwater experiments are conducted based on a UVMS prototype. The UVMS succeeds to autonomously switch different types of valves and handle the pipe. Experiments conducted under dynamic currents validated the reliability and robustness of the proposed methods. © 1996-2012 IEEE.

关键词： Autonomous underwater operations deep neural network underwater vehicle-manipulator systems (UVMS) visual perception visual servoing

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control of a rehabilitation robotic exoskeleton based on intentional reaching direction

Control of a rehabilitation robotic exoskeleton based on int...

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21st Annual Symposium on Micro-Nano Mechatronics and Human Science, MHS 2010, Micro-Nano GCOE 2010, Bio-Manipulation 2010

作者： Huo, Weiguang Huang, Jian Wang, Yongji Wu, Jun Key Lab of Image Processing and Intelligent Control Department of Control Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781424479962

An upper limb robotic exoskeleton of three degrees of freedom (DOF) is designed for the patients who survived stroke and the elderly who have not enough strength to move their limbs freely. Particular attention is paid to the realization of a intention-driven robotic control approach, by which the robotic exoskeleton can assist the user moving his/her arm freely to where he/she intends to go. A force sensing system made of multiple force sensing resisters (FSRs) is embedded in the robotic exoskeleton. A static force model of the upper limb in a relaxed state is obtained when the user wears the exoskeleton. A hybrid model is proposed to describe the behavior modes of human upper limb motion. Filtering technology is designed to infer the intended moving direction of upper limb based on the measured force information and the static force model. The motion intention of user's upper limb can be online estimated using the filter and a mode transition detector. Guided by the inferred intention, an admittance control strategy is assumed to control the motors of each DOF. The effectiveness of proposed robotic system and control approaches is evaluated by experiments. ©2010 IEEE.

关键词： Degrees of freedom (mechanics)

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Indoor localization with incomplete observation using set-membership filter

Indoor localization with incomplete observation using set-me...

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International Symposium on Micro-NanoMechatronics and Human Science, MHS 2015

作者： Wang, Yuan Huang, Jian Key Lab of Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781479966783

Indoor localization is a popular topic because of the poor performance of GPS in the indoor environment. This paper has provided a new method to achieve the goal of indoor localization. Combining the usage of posture sensors with the Radio Frequency Identification (RFID) technology, we solved the problem of plentiful tags in the traditional RFID indoor localization. The relative localization subsystem is based on posture sensors and the absolute localization subsystem is based on RFID. A set-membership theory based data fusion algorithm is proposed to fuse the data of relative localization and absolute localization. Experimental results show that the proposed data fusion algorithm could significantly reduce the accumulated error of our indoor localization system. © 2015 IEEE.

关键词： Indoor positioning systems

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Real-time target tracking with particle filter in moving monocular camera

Real-time target tracking with particle filter in moving mon...

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5th International Symposium on Multispectral image processing and Pattern Recognition

作者： Liu, Guocheng Wang, Yongji Huazhong Univ Sci & Technol Key Lab Image Processing & Intelligent Control Chinese Educ Minist Wuhan 430072 Peoples R China

ISBN: (纸本)9780819469502

In this paper, we propose an improved particle filter algorithm for real-time tracking a randomly moving target in dynamic environment with a moving monocular camera. For making the tracking task robustly and effectively, color histogram based target model is integrated into particle filter algorithm. Bhattacharyya distance is used to weight samples by calculating each sample's histogram with a specified target model and it makes the measurement matching and samples' weight updating more reasonable. In order to reduce sample depletion, the improved algorithm will be able to take the latest observation into account. The experimental results confirm that the method is effective even when the monocular camera is moving and the target object is partially occluded in a clutter background.

关键词： visual tracking particle filter state-space model

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A general end-to-end diagnosis framework for manufacturing systems

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National Science Review 2020年第2期7卷 418-429页

作者： Ye Yuan Guijun Ma Cheng Cheng Beitong Zhou Huan Zhao Hai-Tao Zhang Han Ding School of Artificial Intelligence and Automation MOE Key Lab of Intelligent Control and Image Processing Huazhong University of Science and Technology State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology

The manufacturing sector is envisioned to be heavily influenced by artificial-intelligence-based technologies with the extraordinary increases in computational power and data volumes. A central challenge in the manufacturing sector lies in the requirement of a general framework to ensure satisfied diagnosis and monitoring performances in different manufacturing applications. Here, we propose a general data-driven,end-to-end framework for the monitoring of manufacturing systems. This framework, derived from deep-learning techniques, evaluates fused sensory measurements to detect and even predict faults and wearing conditions. This work exploits the predictive power of deep learning to automatically extract hidden degradation features from noisy, time-course data. We have experimented the proposed framework on 10 representative data sets drawn from a wide variety of manufacturing applications. Results reveal that the framework performs well in examined benchmark applications and can be applied in diverse contexts,indicating its potential use as a critical cornerstone in smart manufacturing.

关键词： manufacturing systems deep learning diagnosis and monitoring

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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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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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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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