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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Journal ArticleDOI
Optical techniques for multiscale damage assessment
TL;DR: In this article, the authors present several geohazard studies with a broad range of scales, from regional to local component, and show that recently developed change detection algorithms can quickly provide regional damage information if...
Journal ArticleDOI
NORCAMA: Change analysis in SAR time series by likelihood ratio change matrix clustering
TL;DR: In this paper, a likelihood ratio test based method of change detection and classification for synthetic aperture radar (SAR) time series, namelyNORmalized Cut on chAnge criterion MAtrix (NORCAMA), is presented.
Journal ArticleDOI
Post-Processing Approach for Refining Raw Land Cover Change Detection of Very High-Resolution Remote Sensing Images
TL;DR: Quantitative evaluations show that the proposed OBEM post-processing approach can achieve better performance and higher accuracies than several commonly used preprocessing methods.
Journal ArticleDOI
Object-level change detection with a dual correlation attention-guided detector
TL;DR: This study proposes an object-level change detection framework to detect changed geographic entities by paying more attention to the overall characteristics and context association of changed object instances by way of dual correlation attention-guided detector.
Journal ArticleDOI
Automated semantic analysis of changes in image sequences of neurons in culture
TL;DR: This paper describes a highly automated approach that not only detects the interesting changes selectively, but also generates quantitative analyses at multiple levels of detail, accomplishing in minutes what it would take an expert hours to complete.
References
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Journal ArticleDOI
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
Stuart Geman,Donald Geman +1 more
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TL;DR: In this article, the authors provide comprehensive background material and explain how to apply the methods and implement the algorithms directly in a unified framework, including geometric principles and how to represent objects algebraically so they can be computed and applied.
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Journal ArticleDOI
Image registration methods: a survey
Barbara Zitová,Jan Flusser +1 more
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.