<プレプリント>
Supervised image classification in Markov random field models with Jeffreys divergence

作成者
本文言語
出版者
発行日
収録物名
出版タイプ
アクセス権
関連情報
概要 We consider supervised image classification based on Markov Random Fields (MRFs), which are derived by the Jeffreys divergence between class-conditional probability densities. It is shown that the MRF... gives an extension of Switzer’s smoothing method for classification. Further, the exact error rate due to the MRF is obtained in a simple setup, and several properties of the classification are derived. Our procedure is applied to two multispectral images, and shows a good performance.続きを見る

本文ファイル

2004-17 pdf 323 KB 86  

詳細

レコードID
査読有無
注記
タイプ
登録日 2009.04.22
更新日 2018.02.19

この資料を見た人はこんな資料も見ています