Journal ArticleDOI
Image change detection algorithms: a systematic survey
TLDR
In this paper, the authors present a systematic survey of the common processing steps and core decision rules in modern change detection algorithms, including significance and hypothesis testing, predictive models, the shading model, and background modeling.Abstract:
Detecting regions of change in multiple images of the same scene taken at different times is of widespread interest due to a large number of applications in diverse disciplines, including remote sensing, surveillance, medical diagnosis and treatment, civil infrastructure, and underwater sensing. This paper presents a systematic survey of the common processing steps and core decision rules in modern change detection algorithms, including significance and hypothesis testing, predictive models, the shading model, and background modeling. We also discuss important preprocessing methods, approaches to enforcing the consistency of the change mask, and principles for evaluating and comparing the performance of change detection algorithms. It is hoped that our classification of algorithms into a relatively small number of categories will provide useful guidance to the algorithm designer.read more
Citations
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Book ChapterDOI
How Far Can You Get by Combining Change Detection Algorithms
TL;DR: Results demonstrate that starting from simple algorithms the proposed IUTIS combination strategy can achieve comparable results with respect to more complex state-of-the-art change detection algorithms, while keeping the computational complexity affordable for real-time applications.
Journal ArticleDOI
Change Detection of Deforestation in the Brazilian Amazon Using Landsat Data and Convolutional Neural Networks
Pablo Pozzobon de Bem,Osmar Abílio de Carvalho Júnior,Renato Fontes Guimarães,Roberto Arnaldo Trancoso Gomes +3 more
TL;DR: This study attempted to map the deforestation between images approximately one year apart, specifically between 2017 and 2018 and between 2018 and 2019, and found that the DL models were better in most performance metrics including the Kappa index, F1 score, and mean intersection over union (mIoU) measure.
Journal ArticleDOI
Automated defect detection for sewer pipeline inspection and condition assessment
TL;DR: In this paper, the authors present the findings of a research project that seeks to enable automated detection of defects in sewer pipelines from inspection videos and images, and present the need for and the challenges of automated defect detection in sewer infrastructure condition monitoring.
Journal ArticleDOI
A New Multivariate Statistical Model for Change Detection in Images Acquired by Homogeneous and Heterogeneous Sensors
TL;DR: This paper proposes a new approach for similarity measurement between images acquired by heterogeneous sensors that exploits the considered sensor physical properties and specially the associated measurement noise models and local joint distributions.
Journal ArticleDOI
Hyperspectral Change Detection in the Presenceof Diurnal and Seasonal Variations
TL;DR: The results indicate that spectral change detection techniques can provide markedly improved performance when the environmental conditions associated with the image pairs are substantially different, and the impacts on clutter suppression and change detection are quantified and compared.
References
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Journal ArticleDOI
Image registration methods: a survey
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TL;DR: A review of recent as well as classic image registration methods to provide a comprehensive reference source for the researchers involved in image registration, regardless of particular application areas.