Image classification using spectral and spatial information based on MRF models
نویسندگان
چکیده
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.
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ورودعنوان ژورنال:
- IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
دوره 4 9 شماره
صفحات -
تاریخ انتشار 1995