title: Image classification using spectral and spatial information based on MRF models.
abstract: A new criterion for classifying multispectral remote sensing images or textured images by using spectral and spatial information is proposed. The images are modeled with a hierarchical Markov Random Field (MRF) model that consists of the observed intensity process and the hidden class label process. The class labels are estimated according to the maximum a posteriori (MAP) criterion, but some reasonable approximations are used to reduce the computational load. A stepwise classification algorithm is derived and is confirmed by simulation and experimental results.
authors.affiliation: Commun. Res. Lab., Kansai Adv. Res. Center, Kobe.
authors.forename: T
authors.initials: T
authors.lastname: Yamazaki
authors.forename: D
authors.initials: D
authors.lastname: Gingras