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http://dx.doi.org/10.5626/JCSE.2014.8.2.65

An Object-Level Feature Representation Model for the Multi-target Retrieval of Remote Sensing Images  

Zeng, Zhi (Huizhou University, Computer Science)
Du, Zhenhong (Zhejiang University, Earth Science)
Liu, Renyi (Zhejiang University, Earth Science)
Publication Information
Journal of Computing Science and Engineering / v.8, no.2, 2014 , pp. 65-77 More about this Journal
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.
Keywords
Remote sensing; Image processing; Spatial representation; 9DLT; Content-based remote sensing image retrieval;
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