Image change detection algorithms: a systematic survey
Rensselaer Polytechnic Institute
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…
Citation impact
- FWCI
- 144.27
- Percentile
- 100%
- References
- 137
Authors
4Topics & keywords
- Change detection
- Computer science
- Preprocessor
- Algorithm
- Data mining
- Artificial intelligence
- Machine learning
- Image processing
- Industry, innovation and infrastructure