changedetection in images or video sequences is used to detect anomalies or important variations in the scene. Although much research has focused on changedetection in surveillance videos, there is little work relat...
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ISBN:
(纸本)9781509057672
changedetection in images or video sequences is used to detect anomalies or important variations in the scene. Although much research has focused on changedetection in surveillance videos, there is little work related to changedetection on aerial or satellite imagery. This paper presents a deep learning approach for changedetection 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.
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...
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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 changedetection performances suggests that the method is able to provide accurate change maps, although possibly affected by misregistration errors or calibration/acquisition artifacts
The paper proposes a novel technique for robust changedetection based upon the integration of intensity and texture differences between two frames. A new texture difference measure based on the relations between grad...
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ISBN:
(纸本)0769512720
The paper proposes a novel technique for robust changedetection 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 changedetection, one can obtain much better segmentation results than using the intensity or structure difference alone.
The main objective of this study is to introduce and evaluate a SAR-based flood mapping algorithm enabling the automatic generation of a large-scale flood record from the ENVISAT ASAR data archive. The flood mapping a...
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The main objective of this study is to introduce and evaluate a SAR-based flood mapping algorithm enabling the automatic generation of a large-scale flood record from the ENVISAT ASAR data archive. The flood mapping algorithm is based on a changedetection approach and requires an automatic selection of optimal reference images. The flood mapping algorithm is applied to selected pairs of images to sequentially generate a record of flood extent maps. False alarms caused by water-like areas are reduced using auxiliary data sources such as the Height Above Nearest Drainage (HAND) index derived from topography data. The proposed method is applied to several ENVISAT WS ASAR datasets acquired over the UK and results are validated with a flood extent map derived from aerial photography. Results presented in this paper demonstrate the effectiveness of the methodology.
change-detection represents a powerful tool for monitoring the evolution of the Earth's surface by multitemporal remote-sensing imagery. Here, a multiscale approach is proposed, in which observations at coarser an...
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change-detection represents a powerful tool for monitoring the evolution of the Earth's surface by multitemporal remote-sensing imagery. Here, a multiscale approach is proposed, in which observations at coarser and finer scales are jointly exploited, and a multiscale contextual unsupervised change-detection method is developed for optical images. Discrete wavelet transforms are applied to extract multiscale features that discriminate changed and unchanged areas and Markovian data fusion is used to integrate both these features and the spatial contextual information in the change-detection process. Unsupervised statistical learning methods (expectation-maximization and Besag's algorithms) are used to estimate the model parameters. Experiments on burnt-forest area detection in multitemporal Landsat TM images are presented.
A new active fire event detection algorithm for data collected with the Spinning Enhanced Visible and Infrared Imager (SE-VIRI) sensor, based on the extended Kalman filter, is introduced. Instead of using the observed...
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A new active fire event detection algorithm for data collected with the Spinning Enhanced Visible and Infrared Imager (SE-VIRI) sensor, based on the extended Kalman filter, is introduced. Instead of using the observed temperatures of the spatial neighbours of a pixel to detect anomalous temperatures, the new algorithm only considers previous observations at the current pixel. The algorithm harnesses the Kalman filter to obtain a prediction of the expected brightness temperature at a given location, which is then compared to the actual SE-VIRI observation. An adaptive threshold is used to determine whether the observed difference is indicative of a potential fire event. Initial tests show that the performance of this method is comparable to that of the EUMETSAT FIR product.
The features of remote sensing imagery like the large amount of data and the changeful of terrain features decide the complexity of the changedetection technology. In allusion to the requirement of the efficiency and...
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The features of remote sensing imagery like the large amount of data and the changeful of terrain features decide the complexity of the changedetection technology. In allusion to the requirement of the efficiency and the precision for large-scale detection, at the base of the conclusions of the changedetection technology all over the world, the key point is to study an algorithm of fast changedetection based on feature library of remote sensing imagery. Under the high performance colony parallel processing environment, taking the incorporate changedetection 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 changedetection. 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 changedetection. 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 changedetection.
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 chang...
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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 changedetection binary image. Different approaches to get the changedetection images are presented. The performances of the implemented algorithms are presented by using ROC curves.
An incremental inductive learning and changedetection method is proposed which generates rule sets that contain general rules underling the observed data and detects changes in them. Unlike most of other algorithms, ...
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An incremental inductive learning and changedetection method is proposed which generates rule sets that contain general rules underling the observed data and detects changes in them. Unlike most of other algorithms, the method is an incremental algorithm that generates the rule set in the course of data observation. The method is motivated by a demand for an automatic procedure for quick modeling of systems subject to change and detecting the changes. The method starts with a most general rule and performs specialization of the rules when a conflicting piece of data is observed. Also the unification of over-specialized rules is done to enhance the generality. The changedetection is based on a statistical hypothesis test of a change in error rate of the rule set assuming randomness in the data presentation order. Simulation studies have been carried out on a toy problem, where a cat observes a mouse and builds a rule set describing the mouse's behavior while the mouse disappears and a new one comes in. The results show that the method can yield a general rule set and that it can successfully detect the change of the mice.
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