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检索条件"主题词=change detection algorithms"

共 1588 条记录，以下是411-420 订阅

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Primal sketch of image series with edge preserving filtering application to change detection

Primal sketch of image series with edge preserving filtering...

引用

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

作者： May Stephane Pelletier Charlotte CNES DCT/SI Belin France CESBIO Belin France

This paper proposes an original approach to the problem of change detection into multitemporal image series. A primal sketch of the image is achieved with a modified Perona-Malik filter: relevant edges are extracted. Then, an application to change detection is proposed. The algorithm related to sketch outputs is performed through density of pixels images. It offers significant information about events that occurred between several acquisitions. Potential of the algorithm on high resolution images is shown, and limitations on very high resolution are explained.

关键词： Image edge detection Time series analysis change detection algorithms Image resolution Algorithm design and analysis Noise Vegetation mapping

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Superpixel-based change detection in high resolution sar images using region covariance features

Superpixel-based change detection in high resolution sar ima...

引用

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

作者： Xiaojing Huang Wen Yang Gui-Song Xia Mingsheng Liao School of Electronic Information Wuhan University Wuhan China State Key Laboratory of LIESMARS Wuhan University Wuhan China

ISBN: (纸本)9781467371209

Feature representation is very important for high resolution synthetic aperture radar (SAR) image interpretation, especially for unsupervised change detection. In this paper we propose a superpixel-based change detection approach that utilize region covariance as feature representation. After segmenting SAR images into superpixels, the second order statistic of SAR feature vectors, i.e., the region covariance feature is extracted for each superpixel. In the difference map generation stage, the dissimilarities of corresponding superpixel pairs in multitemporal SAR images are measured by calculating the Bartlett distances between region covariance features. After that, an adaptive thresholding method is applied to obtain the final detection results. Two multi-temporal TerraSAR-X high resolution SAR image sets are tested for the proposed approach and promising results are achieved.

关键词： Feature extraction Image segmentation Synthetic aperture radar Histograms Covariance matrices Image resolution change detection algorithms

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Image analysis for video surveillance based on spatial regularization of a statistical model-based change detection

Image analysis for video surveillance based on spatial regul...

引用

International Conference on Image Analysis and Processing

作者： F. Ziliani A. Cavallaro Signal Processing Laboratory Swiss Federal Institute of Technology Lausanne Switzerland

Advanced video surveillance applications require two successive steps: image analysis and content understanding. The first step analyses and extracts the characteristics of the video sequence. It defines the regions or the objects of interest according to their spatial/temporal properties. This analysis results in a segmentation of the video sequence. This is interpreted by the content understanding step according to the specific scenario and surveillance requirements. This paper addresses the image analysis problem for a video surveillance system. We use a statistical model-based change detection technique that defines the areas of interest in the image. Each area is analyzed separately by integrating spatial and temporal descriptors in a multi-feature clustering algorithm. The selective procedure we propose minimizes the computational load and significantly improves the results provided by the change detection technique. We test this method on both indoor and outdoor surveillance sequences. All the results show a correct segmentation of the scene. Moreover each object defined in the segmentation is described in terms of its spatial and temporal properties. These results can represent a valid input for a later content understanding procedure in several surveillance scenarios.

关键词： Image analysis Video surveillance Image sequence analysis Video sequences Image segmentation Algorithm design and analysis change detection algorithms Clustering algorithms Testing Layout

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Superpixel Edge Refinement and Differential Feature Enhancement for Transformer-Based Remote Sensing Image change detection

Superpixel Edge Refinement and Differential Feature Enhancem...

引用

Robotics, Intelligent Control and Artificial Intelligence (RICAI), International Conference on

作者： Jingjing Liang Xinlin Xie Tihao Cui Haoxue Zhang Shanxi Provincial Key Laboratory of Advanced Control and Industrial Intelligence School of Electronic Information Engineering Taiyuan University of Science and Technology Taiyuan China

ISBN: (数字)9798331541699

ISBN: (纸本)9798331541705

change detection in remote sensing images is a challenging task, particularly when identifying small and complex objects such as buildings. The task is often hindered by issues such as high fragmentation rates, blurred edges, and elevated false and missed detection rates. These issues arise due to the inherent complexity of the scenes and the problem of class imbalance. To address these challenges, we propose a superpixel edge refinement and differential feature enhancement for Transformer-based change detection networks. First, a region-enhanced Transformer encoder is introduced, incorporating a superpixel edge refinement module. This module leverages pixel-level features extracted by the Transformer to generate superpixel feature embeddings, thereby enhancing local and edge information. Second, a differential feature enhancement module is designed to emphasize true change regions while suppressing pseudo-change areas. This is achieved through a dual-branch structure comprising feature enhancement and change extraction, further augmented by a saliency module. Finally, a Dice loss function is employed as an auxiliary loss term, complementing the cross-entropy loss in the construction of an edge-optimized loss function. The resulting loss function aims to balance overall detection accuracy with edge refinement. The proposed algorithm was evaluated on the widely used datasets LEVIR-CD and DSIFN-CD. Compared to existing algorithms, the proposed method effectively improved edge detail and overall consistency while maintaining detection accuracy. Additionally, false detections and missed detections were reduced.

关键词： Measurement Accuracy change detection algorithms Image edge detection Buildings Feature extraction Transformers Object recognition Remote sensing Robots

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Self-adaptive hybrid PSO-GA method for change detection under varying contrast conditions in satellite images

Self-adaptive hybrid PSO-GA method for change detection unde...

引用

Science and Information Conference (SAI)

作者： Huseyin Kusetogullari Amir Yavariabdi Department of Computer Science and Engineering Blekinge Institute of Technology Karlskrona Sweden Department of Mechatronics Engineering KTO Karatay University Konya Turkey

ISBN: (纸本)9781467384612

This paper proposes a new unsupervised satellite change detection method, which is robust to illumination changes. To achieve this, firstly, a preprocessing strategy is used to remove illumination artifacts and results in less false detection than traditional threshold-based algorithms. Then, we use the corrected input data to define a new fitness function based on the difference image. The purpose of using Self-Adaptive Hybrid Particle Swarm Optimization-Genetic Algorithm (SAPSOGA) is to combine two meta-heuristic optimization algorithms to search and find the feasible solution in the NP-hard change detection problem rapidly and efficiently. The hybrid algorithm is employed by letting the GA and PSO run simultaneously and similarities of GA and PSO have been considered to implement the algorithm, i.e. the population. In the SAPSOGA employed, in each iteration/generation the two population based algorithms share different amount of information or individual(s) between themselves. Thus, each algorithm informs each other about their best optimum results (fitness values and solution representations) which are obtained in their own population. The fitness function is minimized by using binary based SAPSOGA approach to produce binary change detection masks in each iteration to obtain the optimal change detection mask between two multi temporal multi spectral landsat images. The proposed approach effectively optimizes the change detection problem and finds the final change detection mask.

关键词： Satellites change detection algorithms Sociology Statistics Lighting Genetic algorithms Cost function

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Optimal Quickest change detection in Sensor Networks Using Ordered Transmissions

Optimal Quickest Change Detection in Sensor Networks Using O...

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IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

作者： Yicheng Chen Rick S. Blum Brian M. Sadler Lehigh University Bethlehem PA USA Army Research Laboratory MD USA

ISBN: (数字)9781728154787

ISBN: (纸本)9781728154794

Quickest change detection in a sensor network is considered where each sensor observes a sequence of random variables and transmits its local information on the observations to a fusion center. At an unknown point in time, the distribution of the observations at all sensors changes. The objective is to detect the change in distribution as soon as possible, subject to a false alarm constraint. We consider minimax formulations for this problem and propose a new approach where transmissions are ordered and halted when sufficient information is accumulated at the fusion center. We show that the proposed approach can achieve the optimal performance equivalent to the centralized cumulative sum (CUSUM) algorithm while requiring fewer sensor transmissions. Numerical results for a shift in mean of independent and identically distributed Gaussian observations show significant communication savings for the case where the change seldom occurs which is frequently true in many important applications.

关键词： Signal processing algorithms Delays Signal processing change detection algorithms Indexes Conferences Wireless communication

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Adaptive approach for change detection in EMG recordings

Adaptive approach for change detection in EMG recordings

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： W. El Falou A. Khalil J. Duchene Faculty of Engineering Lebanese University Tripoli Lebanon LM2S Universite Technologie Troyes Troyes France

In this paper we present a new algorithm to detect abrupt changes in a signal when there is no a priori knowledge of the hypotheses on the process to be detected. This algorithm is based on the CUSUM algorithm. It can be applied in case of frequency and energy changes. This algorithm works when the samples are dependent and autoregressive modeling is needed. It is used to distinguish EMG segments from noise segments.

关键词： Electromyography Signal processing algorithms change detection algorithms Signal processing Frequency Probability density function Knowledge engineering Event detection Signal to noise ratio Biomedical signal processing

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Land Use and Land Cover change detection using Google Earth Engine

Land Use and Land Cover Change Detection using Google Earth ...

引用

International Conference on Inventive Computation Technologies (ICICT)

作者： Jagannadham Teja Radhesyam Vaddi Kesireddy Lakshmika Parasa Nirupama Department of Information Technology Velagapudi Ramakrishna Siddhartha Engineering College Andhra Pradesh Vijayawada India

ISBN: (数字)9798350359299

ISBN: (纸本)9798350359305

Land use and Land Cover (LULC) usually denotes to the classification of human activities and natural elements on the earth surface within a specific time edge. With the development of remote sensing technology and availability of multispectral data, LULC has become crucial in various applications like urbanization and agriculture. This research study focuses on demarcating cloud enabled remote sensing platform, Google Earth Engine (GEE) along with the use of machine learning algorithms and evaluates the platform’s utility to perform LULC. The multispectral datasets like Landsat-7 and sentinel-2 are used to test the performance. The visualization and analysis on change map between the years 2002-2015 shows the various correctly classified land cover regions.

关键词： Earth Machine learning algorithms Artificial satellites change detection algorithms Urban areas Land surface Internet

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Scene change detection algorithm for MPEG video sequence

Scene change detection algorithm for MPEG video sequence

引用

IEEE International Conference on Image Processing

作者： Jian Feng Kwok-Tung Lo H. Mehrpour School of Electrical Engineering University of New South Wales Australia Department of Electronic Engineering Hong Kong Polytechnic University Hong Kong China

A new scene change detection algorithm is developed for MPEG encoded video sequences. The proposed method is very simple that it only requires the bit-rate information at macroblock level as well as the number of various motion-predicted blocks for detection. Those information can be extracted easily from the encoded bit-stream without decompression. Simulation results on different sequences show that the proposed algorithm is effective for detecting abrupt scene changes in MPEG video.

关键词： Layout detection algorithms Video compression change detection algorithms Video on demand Cameras Video sequences Transform coding Motion detection Data mining

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Robust change-detection by Normalised Gradient-Correlation

Robust Change-Detection by Normalised Gradient-Correlation

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Robert O'Callaghan Tetsuji Haga Visual Information Laboratory Mitsubishi Electric ITE Guildford UK Advanced Technology R&D Center Mitsubishi Electric Corporation Limited Amagasaki Hyogo Japan

A novel algorithm for robustly segmenting changes between different images of a scene is presented. This computationally efficient algorithm is based on a non-linear comparison of gradient structure in overlapping image-regions and offers intrinsic invariance to changing illumination, without recourse to background-model adaptation. High accuracy is demonstrated on test video data with and without illumination changes. The technique is applicable to motion-segmentation as well as measuring longer-term object-changes.

关键词： Robustness Lighting change detection algorithms Application software Layout Pixel Object detection Motion detection Algorithm design and analysis Motion analysis

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