Zhang, Z.; Yang, M.Y.; Zhoua, M.: Multi-source hierarchical conditional random field model for feature fusion of remote sensing images and LiDAR data. In: Heipke, C.; Jacobsen, K.; Rottensteiner, F.; Sörgel, U. (Eds.): ISPRS Hannover Workshop 2013. Katlenburg-Lindau : Copernicus Publications, 2013 (The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; 40-1/W1), S. 389-392. DOI: https://doi.org/10.5194/isprsarchives-XL-1-W1-389-2013
Abstract: | |
Feature fusion of remote sensing images and LiDAR points cloud data, which have strong complementarity, can effectively play the advantages of multi-class features to provide more reliable information support for the remote sensing applications, such as object classification and recognition. In this paper, we introduce a novel multi-source hierarchical conditional random field (MSHCRF) model to fuse features extracted from remote sensing images and LiDAR data for image classification. Firstly, typical features are selected to obtain the interest regions from multi-source data, then MSHCRF model is constructed to exploit up the features, category compatibility of images and the category consistency of multi-source data based on the regions, and the outputs of the model represents the optimal results of the image classification. Competitive results demonstrate the precision and robustness of the proposed method. | |
License of this version: | CC BY 3.0 Unported |
Document Type: | BookPart |
Publishing status: | publishedVersion |
Issue Date: | 2013 |
Appears in Collections: | Fakultät für Elektrotechnik und Informatik |
pos. | country | downloads | ||
---|---|---|---|---|
total | perc. | |||
1 | Germany | 130 | 67.36% | |
2 | United States | 24 | 12.44% | |
3 | China | 17 | 8.81% | |
4 | No geo information available | 5 | 2.59% | |
5 | Poland | 3 | 1.55% | |
6 | Korea, Republic of | 2 | 1.04% | |
7 | Austria | 2 | 1.04% | |
8 | Vietnam | 1 | 0.52% | |
9 | Mexico | 1 | 0.52% | |
10 | Italy | 1 | 0.52% | |
other countries | 7 | 3.63% |
Hinweis
Zur Erhebung der Downloadstatistiken kommen entsprechend dem „COUNTER Code of Practice for e-Resources“ international anerkannte Regeln und Normen zur Anwendung. COUNTER ist eine internationale Non-Profit-Organisation, in der Bibliotheksverbände, Datenbankanbieter und Verlage gemeinsam an Standards zur Erhebung, Speicherung und Verarbeitung von Nutzungsdaten elektronischer Ressourcen arbeiten, welche so Objektivität und Vergleichbarkeit gewährleisten sollen. Es werden hierbei ausschließlich Zugriffe auf die entsprechenden Volltexte ausgewertet, keine Aufrufe der Website an sich.