An image change detection algorithm based on Markov random field models

Author

Kasetkasem, Teerasit ; Varshney, Pramod Kumar

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., Syracuse Univ., NY, USA

Volume

40

Issue

8

fYear

2002

fDate

8/1/2002 12:00:00 AM

Firstpage

1815

Lastpage

1823

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.

Keywords

Markov processes; geophysical signal processing; image processing; maximum likelihood estimation; remote sensing; MAP criterion; MRF models; Markov random field models; change images; image change detection algorithm; maximum a posteriori criterion; noiseless images; optimum ICD algorithm; remote sensing; Change detection algorithms; Character recognition; Computational Intelligence Society; Detection algorithms; Helium; Image recognition; Image texture analysis; Layout; Markov random fields; Pixel;

fLanguage

English

Journal_Title

Geoscience and Remote Sensing, IEEE Transactions on

Publisher

ieee

ISSN

0196-2892

Type

jour

DOI

10.1109/TGRS.2002.802498

Filename

1036009