Probabilistic image processing based on the Q-Ising model by means of the mean-field method and loopy belief propagation

Kazuyuki Tanaka, D. M. Titterington

研究成果: Conference article査読

2 被引用数 (Scopus)

抄録

The framework is presented of Bayesian image restoration for multi-valued images by means of the Q-Ising model. Hyperparameters in the probabilistic model are determined so as to maximize the marginal likelihood. Practical algorithms are described based the conventional mean-field approximation and loopy belief propagation. We compare the results empirically with those provided by conventional filters and the new methods are found to be superior.

本文言語English
ページ(範囲)40-43
ページ数4
ジャーナルProceedings - International Conference on Pattern Recognition
2
出版ステータスPublished - 2004 12 17
イベントProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom
継続期間: 2004 8 232004 8 26

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識

フィンガープリント

「Probabilistic image processing based on the Q-Ising model by means of the mean-field method and loopy belief propagation」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル