학술논문

An Object-Level Feature Representation Model for the Multi-target Retrieval of Remote Sensing Images
Document Type
Academic Journal
Source
Journal of Computing Science and Engineering. 2014-06 8(2):65-77
Subject
Remote sensing
Image processing
Spatial representation
9DLT
Content-based remote sensing image retrieval
Language
Korean
ISSN
1976-4677
2093-8020
Abstract
To address the problem of multi-target retrieval (MTR) of remote sensing images, this study proposes a new object-level feature representation model. The model provides an enhanced application image representation that improves the efficiency of MTR. Generating the model in our scheme includes processes, such as object-oriented image segmentation, feature parameter calculation, and symbolic image database construction. The proposed model uses the spatial representation method of the extended nine-direction lower-triangular (9DLT) matrix to combine spatial relationships among objects, and organizes the image features according to MPEG-7 standards. A similarity metric method is proposed that improves the precision of similarity retrieval. Our method provides a trade-off strategy that supports flexible matching on the target features, or the spatial relationship between the query target and the image database. We implement this retrieval framework on a dataset of remote sensing images. Experimental results show that the proposed model achieves competitive and high-retrieval precision.