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检索条件"主题词=change detection algorithms"

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change detection using multiscale segmentation and Kullback-Leibler divergence: Application on road damage extraction

Change detection using multiscale segmentation and Kullback-...

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International Workshop on the Analysis of Multi-temporal Remote Sensing Images (MultiTemp)

作者： Moslem Ouled Sghaier Richard Lepage Ecole de technologie supérieure Montréal Québec Canada

This paper addresses the problem of change detection from very high resolution remotely sensed images and its application on road damage extraction in case of major disaster. The proposed methodology is based on the multiscale image segmentation using the Haar wavelet in order to define the appropriate unit of analysis for the comparison step. The Kullback-Leibler divergence is then applied as a similarity measurement to identify changed regions. This strategy is adapted to solve the road damage extraction problem by applying the Dempster-Shafer theory (DST). The images acquired during the earthquake that hits Port-au-Prince (Haiti) on 12 January 2010 are used in the experimentations and the obtained results demonstrate the accuracy and the efficiency of the described method.

关键词： Image segmentation Roads Remote sensing change detection algorithms Image edge detection Image resolution Noise

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Subpixel change detection Based on Abundance and Slope Features

Subpixel Change Detection Based on Abundance and Slope Featu...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： C.-C. Hsieh P.-F. Hsieh C.-W. Lin Department of Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan

Most of change detection algorithms for multi-temporal images are performed in unit of pixels. Due to the limit of spatial resolution, a pixel is, in many cases, a mixed pixel that contains more than one ground cover types. In order to explore more information from images, we have reviewed several spectral unmixing algorithms and used them to accomplish subpixel change detection. In an application of landslide monitoring, we demonstrated the use of subpixel change detection for detection of landslide spreading. We used spectral unmixing algorithms to extract the abundance information from multispectral images. For the particular characteristic of landslides, we incorporated the slope feature into process. Our preliminary result shows that the subpixel change detection method can provide more detailed information about landslide spread than pixel-based change detection algorithms.

关键词： Terrain factors change detection algorithms Vegetation mapping Soil Remote sensing detection algorithms Pixel Matrix decomposition Spatial resolution Data mining

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Automatic change detection based on conditional random field in high resolution remote sensing images

Automatic change detection based on conditional random field...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Guo Cao Xuesong Li Yanfeng Shang The School of Computer Science and Technology Nanjing University of Science and Technology Nanjing China The third research institute of ministry of public security Shanghai China

An automatic change detection method based on conditional random field (CRF) is presented for high resolution remote sensing images in this paper. Marginalized denoising autoencoder is used to generate the difference image. The clustering results of Fuzzy C-means are applied to initialize the unary potentials of CRF. A scaled squared Euclidean distance between neighboring pixels in the observed images is introduced to define the pairwise potentials of CRF, which avoid training parameters and help improve the accuracy and the degree of automation. The experimental results obtained on different remote sensing images demonstrated the accuracy and efficiency of our proposed method.

关键词： Remote sensing change detection algorithms Training Classification algorithms Labeling Image resolution Kernel

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Unsupervised change detection using Spatial Transformer Networks

Unsupervised change detection using Spatial Transformer Netw...

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Western New York Image Processing Workshop (WNYIPW)

作者： Dan Chianucci Andreas Savakis Department of Computer Engineering Rochester Institute of Technology Rochester New York

ISBN: (纸本)9781509057672

change detection in images or video sequences is used to detect anomalies or important variations in the scene. Although much research has focused on change detection in surveillance videos, there is little work related to change detection on aerial or satellite imagery. This paper presents a deep learning approach for change detection in satellite images. The proposed approach utilizes Spatial Transformer Networks (STNs) which learn to perform a coordinate transformation to localize potential change regions. With unsupervised training the STN system examines differences between images for significant change activity. Our initial results illustrate the merit of this method.

关键词： Training change detection algorithms Neural networks Machine learning Filtering algorithms Prediction algorithms Satellites

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Unsupervised change-detection in Color Fundus Images of the Human Retina

Unsupervised Change-Detection in Color Fundus Images of the ...

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Proceedings of the Nordic Signal Processing Symposium (NORSIG)

作者： A. Nappo J. A. Benediktsson S. B. Serpico S. R. Joelsson G. Moser R. A. Karlsson G. H. Halldorsson S. H. Hardarson E. Stefansson Department of Biophysical and Electronic Engineering (DIBE) University of Genoa Genoa Italy Department of Electrical and Computer Engineering and Department of Ophthalmology University of Iceland Reykjavik Iceland

The aim of this paper is to develop an automatic method for the detection of the changes that occurred in multitemporal digital images of the fundus of the human retina, in terms of white and red spots. The images are acquired from the same patient at different times by a color fundus camera. The proposed approach is unsupervised and is based on a minimum-error thresholding technique. This technique is applied both to separate the "change" and the "no-change" classes in a suitably defined difference image, and to distinguish among different typologies of change. The algorithm is tested on 10 multitemporal pairs of images. A quantitative assessment of the change detection performances suggests that the method is able to provide accurate change maps, although possibly affected by misregistration errors or calibration/acquisition artifacts

关键词： Humans Retina change detection algorithms Diseases Retinopathy Pixel Optical sensors Optical noise Electronic mail Digital images

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Matrix CUSUM: a recursive multi-hypothesis change detection algorithm

Matrix CUSUM: a recursive multi-hypothesis change detection ...

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IEEE International Symposium on Information Theory

作者： T. Oskiper H.V. Poor Department of Electrical Engineering Princeton University Princeton NJ USA

A new recursive M-ary change detection algorithm is described.

ISBN: (纸本)0780371232

A new recursive M-ary change detection algorithm is described.

关键词： detection algorithms Iron Distribution functions change detection algorithms Delay Random variables Algorithm design and analysis Minimax techniques Statistical distributions Density functional theory

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Abrupt scene change detection based on the temporal activity distributions

Abrupt scene change detection based on the temporal activity...

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IEEE Asia-Pacific Conference on Circuits and Systems

作者： Jae Ho Chung Department of Electronic Engineering Inha University Incheon South Korea

ISBN: (纸本)0780337026

In this paper, an abrupt scene change detection algorithm is suggested. The algorithm is developed based on the temporal activity distribution that derived from the temporal subband analysis. Computer simulation results show that the proposed scheme is capable of detecting abrupt scene changes in video sequence accurately and efficiently.

关键词： Layout Frequency detection algorithms Image analysis Image sequence analysis Video sequences Performance analysis Signal analysis change detection algorithms Algorithm design and analysis

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change detection methods for automatic scene analysis by using mobile surveillance cameras

Change detection methods for automatic scene analysis by usi...

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IEEE International Conference on Image Processing

作者： L. Marcenaro F. Oberti C.S. Regazzoni DIBE Department of Biophysical and Electronic Engineering University of Genoa Italy Universita degli Studi di Genova Genova Liguria IT

ISBN: (纸本)0780362977

This paper proposes a video-surveillance system based on a mobile camera. In particular the developed system creates (during the off-line phase) a panoramic multilayer background image allowing one to use common change detection algorithms to search for a change detection binary image. Different approaches to get the change detection images are presented. The performances of the implemented algorithms are presented by using ROC curves.

关键词： Image analysis Surveillance Cameras Layout Nonhomogeneous media Phase detection change detection algorithms Tracking Optical sensors detection algorithms

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A Study of Fast change detection Algorithm Based on Feature Library of Remote Sensing Imagery

A Study of Fast Change Detection Algorithm Based on Feature ...

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International Symposium on Image and Data Fusion (ISIDF)

作者： Yuan Ma Haitao Li Haiyan Gu Institute of Surveying and Geography Science LiaoNing University of Engineering and Technology Fuxin P.R. China Chinese Academy of Surveying and Mapping Key Laboratory of Geo-informatics of State Bureau of Surveying and Mapping Beijing P.R. China

The features of remote sensing imagery like the large amount of data and the changeful of terrain features decide the complexity of the change detection technology. In allusion to the requirement of the efficiency and the precision for large-scale detection, at the base of the conclusions of the change detection technology all over the world, the key point is to study an algorithm of fast change detection based on feature library of remote sensing imagery. Under the high performance colony parallel processing environment, taking the incorporate change detection technical flow and the system frame as the backing, this paper analyzed the features of the representative terrain feature, established a feature library, and studied an algorithm based on the feature library of remote-sensing imagery. With the help of typical terrain samples feature library and classify system, matched the typical samples of the feature library with the object features by full wave bands segmentation and vector analysis, namely, automatically change detection. At last, it realized the change information vector output using the storied overlay strategy. Taking QUICKBIRD of Shenzhen area as the tentative - data, used this method to carry on change detection. The results indicate that this method enhances in the precision and the efficiency obviously compared to the traditional methods. Therefore, it may apply in the practice for the large-scale imagery of change detection.

关键词： Feature extraction Libraries Remote sensing Image segmentation change detection algorithms Accuracy Data mining

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Robust change detection by fusing intensity and texture differences

Robust change detection by fusing intensity and texture diff...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Liyuan Li M.K.H. Leung KRDL RWCP Multi Modal Functions Laboratory Singapore Singapore School of Computer Engineering Nanyang technological University Singapore Singapore

ISBN: (纸本)0769512720

The paper proposes a novel technique for robust change detection based upon the integration of intensity and texture differences between two frames. A new texture difference measure based on the relations between gradient vectors is described. The robustness of the measure with respect to noise and illumination changes has been analyzed. Two ways to integrate the intensity and texture differences are proposed. The first combines two measures according to the weightage of texture evidence, while the second takes into additional constraint of smoothness. The parameters of the algorithm are selected automatically. The computational complexity analysis indicates that the proposed technique can run in real-time. Experimental results show that by exploiting both intensity and texture differences for change detection, one can obtain much better segmentation results than using the intensity or structure difference alone.

关键词： Lighting Noise robustness Image edge detection Motion detection Background noise Noise level Statistical distributions Noise measurement change detection algorithms Computational complexity

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