Abstract
This paper addresses the problem of image change detection (ICD) based on Markov random field (MRF) models. MRF has long been recognized as an accurate model to describe a variety of image characteristics. Here, we use the MRF to model both noiseless images obtained from the actual scene and change images (CIs), the sites of which indicate changes between a pair of observed images. The optimum ICD algorithm under the maximum a posteriori (MAP) criterion is developed under this model. Examples are presented for illustration and performance evaluation.
Original language | English (US) |
---|---|
Pages (from-to) | 1815-1823 |
Number of pages | 9 |
Journal | IEEE Transactions on Geoscience and Remote Sensing |
Volume | 40 |
Issue number | 8 |
DOIs | |
State | Published - Aug 1 2002 |
Keywords
- Change detection
- Markov random fields
- Maximum a posteriori (MAP) criterion
- Multitemporal image analysis
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Earth and Planetary Sciences(all)