Object-Oriented Semisupervised Classification of VHR Images by Combining MedLDA and a Bilateral Filter
Joint Authors
He, Shi
Tang, Hong
Li, Jing
Shu, Yang
Shen, Li
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-11-15
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
A Bayesian hierarchical model is presented to classify very high resolution (VHR) images in a semisupervised manner, in which both a maximum entropy discrimination latent Dirichlet allocation (MedLDA) and a bilateral filter are combined into a novel application framework.
The primary contribution of this paper is to nullify the disadvantages of traditional probabilistic topic models on pixel-level supervised information and to achieve the effective classification of VHR remote sensing images.
This framework consists of the following two iterative steps.
In the training stage, the model utilizes the central labeled pixel and its neighborhood, as a squared labeled image object, to train the classifiers.
In the classification stage, each central unlabeled pixel with its neighborhood, as an unlabeled object, is classified as a user-provided geoobject class label with the maximum posterior probability.
Gibbs sampling is adopted for model inference.
The experimental results demonstrate that the proposed method outperforms two classical SVM-based supervised classification methods and probabilistic-topic-models-based classification methods.
American Psychological Association (APA)
He, Shi& Tang, Hong& Li, Jing& Shu, Yang& Shen, Li. 2015. Object-Oriented Semisupervised Classification of VHR Images by Combining MedLDA and a Bilateral Filter. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1073148
Modern Language Association (MLA)
He, Shi…[et al.]. Object-Oriented Semisupervised Classification of VHR Images by Combining MedLDA and a Bilateral Filter. Mathematical Problems in Engineering No. 2015 (2015), pp.1-8.
https://search.emarefa.net/detail/BIM-1073148
American Medical Association (AMA)
He, Shi& Tang, Hong& Li, Jing& Shu, Yang& Shen, Li. Object-Oriented Semisupervised Classification of VHR Images by Combining MedLDA and a Bilateral Filter. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1073148
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073148