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
The continuous spatio-temporal model CSTM as an exhaustive framework for multi-scale spatio-temporal analysis
TL;DR: The continuous spatio-temporal model (CSTM), a conceptual model that seeks to address the shortcoming of either spatial or temporal attributes in the integration of space and time over multiple scales, is introduced.
Journal ArticleDOI
A review of remote sensing data change detection: Comparison of Faisalabad and Multan Districts, Punjab Province, Pakistan
TL;DR: In this paper, the authors presented an application of the use of Landsat ETM+ images and MODIS EVI/NDVI time-series vegetation phenology algorithms of Faisalabad and Multan districts for evaluation of soil productivity and comparison of temporal change detection.
Proceedings ArticleDOI
A Mixed Markov model for change detection in aerial photos with large time differences
Csaba Benedek,Tamás Szirányi +1 more
TL;DR: A novel multi-layer Mixed Markov model is proposed for detecting relevant changes in registered aerial images taken with significant time differences and ensures optimal local feature selection and smooth, observation-consistent classification.
Journal ArticleDOI
Dynamic Landmarking for Surface Feature Identification and Change Detection
Kiri L. Wagstaff,Julian Panetta,Adnan Ansar,Ronald Greeley,Mary Pendleton Hoffer,Melissa Bunte,Norbert Schorghofer +6 more
TL;DR: To study fresh impact craters, dust devil tracks, and dark slope streaks on Mars, a new approach to orbital image analysis called dynamic landmarking is introduced, which focuses on the identification and comparison of visually salient features in images.
Journal ArticleDOI
Detection and diagnosis of model parameter and noise variance changes with application in seismic signal processing
TL;DR: A new algorithm able to discriminate between the model parameter and noise variance changes is presented and some Monte Carlo simulations for change detection in a second order FIR model and experimental results obtained in analysis of seismic signals are obtained, using the proposed approach.
References
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