Image Classification Based on a Multiresolution Two Dimensional Hidden Markov Model
نویسندگان
چکیده
This paper presents an image classi cation algorithm using a multiresolution two dimensional hidden Markov model (HMM). The multiresolution two dimensional hidden Markov model is an extension from the two dimensional hidden Markov model for image classi cation. A classi er estimates model parameters using the EM algorithm. Classi cation is then performed according to the maximum a posteriori probability criterion. The multiresolution model enables multiscale context information be incorporated into classi cation decisions. Suboptimal classi cation algorithms based on the model provide a progressive classi cation scheme which greatly speeds up classi cation with a single resolution HMM.
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