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The method of image restoration in the environments of dust

The method of image restoration in the environments of dust

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IEEE International Conference on Mechatronics and Automation

作者： Yuanyu Wang Yuanzong Li Tianxu Zhang Department of Computer Fundamental Education TaiYuan University of Technology TaiYuan China College of Mechanical Engineering TaiYuan University of Technology TaiYuan China Institute for Pattern Recognition and A.I State Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology WuHan China

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, a particle swarm optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with dual threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments.

关键词： image edge detection image restoration Degradation Atmospheric modeling Optical scattering Optical imaging

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Study on the Method of image Restoration in the Environment of Dust

Study on the Method of Image Restoration in the Environment ...

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International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Yuanyu Wang Yuanzong Li Tianxu Zhang Department of Computer Fundamental Education Taiyuan University Of Technology Taiyuan China College of Mechanical Engineering Taiyuan University Of Technology Taiyuan China Institute of Pattern Recognition and A.I State Key Laboratory of Image Processing and Intelligent Control HuaZhong University of Science and Technology Wuhan China

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, GA optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with automatic threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments.

关键词： image edge detection image restoration Scattering Degradation Gallium Atmospheric modeling Genetic algorithms

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Evaluating deformation patterns of the thoracic aorta in gated CTA sequences

Evaluating deformation patterns of the thoracic aorta in gat...

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IEEE International Symposium on Biomedical Imaging

作者： Ernst Schwartz Roman Gottardi Johannes Holfeld Christian Loewe Martin Czerny Georg Langs Computational Image Analysis and Radiology Lab (CIR) Medical University of Vienna Austria Pattern Recognition and Image Processing Group University of Technology Vienna Austria Division of Cardiothoracic Surgery Department of Surgery Medical University of Vienna Austria Division of Interventional Radiology Department of Radiology Medical University of Vienna Austria Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology USA

ISBN: (纸本)9781424441259;9781424441266

Cardiovascular interventions in the region of the aortic isthmus such as stent-grafting and vessel transposition introduce substantial changes in the deformation properties of the affected vessels. The changes play a fundamental role in the long-term prognosis for any such treatment, but are only poorly understood to date. We explore a fully automated method to quantify the deformation patterns of the thoracic aorta in gated computed tomography sequences. The aorta is segmented by a level set approach that accurately identifies the vessel lumen in each frame of the sequence. Consequently, landmarks on the vessel wall in each frame are registered using a probabilistic method. This allows for the measurement of global and local deformation properties. We evaluate our method on synthetic datasets and report first results of its application on real world data.

关键词： Biomedical imaging image segmentation Radiology Cardiology Surgery Computed tomography Level set Electrocardiography Pathology Deformable models

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Multichannel image restoration based on optimization of the structural similarity index

Multichannel image restoration based on optimization of the ...

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43rd Asilomar Conference on Signals, Systems and computers

作者： Temerinac-Ott, Maja Burkhardt, Hans Department of Pattern Recognition and Image Processing Institute of Computer Science University of Freiburg Georges-Köhler-Allee Geb. 052 79110 Freiburg Germany University of Freiburg Germany

ISBN: (纸本)9781424458271

In this paper a framework for multichannel image restoration based on optimization of the structural similarity (SSIM) index is presented. The SSIM index describes the similarity of images more appropriately for the human visual system than the mean square error (MSE). It has not yet been explored for the multi channel restoration task. The construction of an optimization algorithm is difficult due to the non-linearity of the SSIM measure. The existing solution based on a quasi-convex problem formulation is successfully extended for the multichannel image restoration. The correctness of the algorithm is verified on sample images and it is shown that multi-view information can significantly improve the restoration results. © 2009 IEEE.

关键词： Convex optimization

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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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2009 Workshop on Applications of computer Vision, WACV 2009

作者： Kong, Qing-Jie Kumar, Avinash Ahuja, Narendra Liu, Yuncai Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign Urbana IL 61801 United States Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9781424454976

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. © 2009 IEEE.

关键词： Containers

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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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2009 IEEE International Conference on Multimedia and Expo, ICME 2009

作者： Xiaowei, Lv Kong, Qing-Jie Fei, Weng Yuncai, Liu Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong Univ. Shanghai China Beckman Institute Department of Electrical and Computer Engineering Univ. of Illinois at Urbana-Champaign Urbana IL United States

ISBN: (纸本)9781424442911

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. ©2009 IEEE.

关键词： Graphic methods

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A shadow detection method for remote sensing images using Affinity Propagation algorithm

A shadow detection method for remote sensing images using Af...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Huaiying Xia Xinyu Chen Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China School of Computer Science and Technology Beijing Institute of Technology Beijing China

Shadow detection in high spatial resolution remote sensing image is very critical for locating geographical targets. In this paper, we proposed a new shadow detection method using Affinity Propagation (AP) algorithm in the Hue-Saturation-Intensity (HSI) color space. Because the pixel matrix is a large-scale matrix, if we apply AP algorithm directly on the raw pixel space, it will be computation intensive to calculate the similarity matrix. To solve this problem, we propose to divide the matrix into several blocks and then applying AP to detect shadows in H, S and I components respectively. Then, three detected images are fused to obtain a final shadow detection result. Comparative experiments are performed for K-means and threshold segmentation methods. The experimental results show that higher detection accuracy of the proposed approach is obtained, and it can solve the problems of false dismissals of K-means and threshold segmentation method.

关键词： Remote sensing image segmentation Space technology Shape Color Layout Histograms image processing Spatial resolution Object detection

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Investigating visual feature extraction methods for image annotation

Investigating visual feature extraction methods for image an...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Rukun Hu Shuai Shao Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China The School of Computer Science and Technology Beijing Institute of Technology Beijing China

In order to investigate the performance of visual feature extraction method for automatic image annotation, three visual feature extraction methods, namely discrete cosine transform, Gabor transform and discrete wavelet transform, are studied in this paper. These three methods are used to extract low-level visual feature vectors from images in a given database separately, then these feature vectors are mapped to high-level semantic words to annotate images with labels in a given semantic label set. As it is more efficient to depict the visual features of an image by the feature distribution than to resort to image segmentation technology for semantic image blocks, this paper is going to find out which of the three feature extraction methods performs better in image annotation based on the distribution of feature vectors from the image. The performance of three different kinds of feature extraction method is fully analyzed, and it is found that discrete cosine transform method is more suitable for Gaussian mixture model in automatic image annotation.

关键词： Feature extraction Discrete wavelet transforms Discrete cosine transforms Shape image databases Spatial databases Visual databases image analysis Performance analysis Bayesian methods

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Mobile Robot Position Identification with Specially Designed Landmarks

Mobile Robot Position Identification with Specially Designed...

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Japan-China Joint Workshop on Frontier of computer science and Technology (FCST)

作者： Huakang Li Long Zheng Jie Huang Chunlei Zhao Qunfei Zhao School of Computer Science and Engineering University of Aizu Aizu-Wakamatsu Japan Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

In this paper, we proposed a visual position calibration method using colored rectangle signboards for a mobile robot which is designed to work in a room environment. The rectangle signboards are placed in several known positions. Using Canny algorithm to detect the edge of color area to calculate the vanishing points in the image of the signboard, it is possible to obtain the relative direction and distance between the signboard and the robot by a single image. Experiments of position calibration were conducted. The results showed this method is effective and the errors between the set up positions and the experimental results were about 1.5 degrees and 3 cm in an array position.

关键词： Mobile robots image edge detection Robot vision systems Cameras Calibration Orbital robotics Navigation Relays computer science Shape

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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

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

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