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Remote Sensing Image Retrieval by Scene Semantic Matching
- Source :
- IEEE Transactions on Geoscience and Remote Sensing. 51:2874-2886
- Publication Year :
- 2013
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2013.
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Abstract
- This paper proposes a remote sensing (RS) image retrieval scheme by using image scene semantic (SS) matching. The low-level image visual features (VFs) are first mapped into multilevel spatial semantics via VF extraction, object-based classification of support vector machines, spatial relationship inference, and SS modeling. Furthermore, a spatial SS matching model that involves the object area, attribution, topology, and orientation features is proposed for the implementation of the sample-scene-based image retrieval. Moreover, a prototype system that uses a coarse-to-fine retrieval scheme is implemented with high retrieval accuracy. Experimental results show that the proposed method is suitable for spatial SS modeling, particularly geographic SS modeling, and performs well in spatial scene similarity matching.
- Subjects :
- business.industry
Computer science
Feature extraction
Pattern recognition
Image segmentation
Support vector machine
Automatic image annotation
Image texture
General Earth and Planetary Sciences
Computer vision
Visual Word
Artificial intelligence
Electrical and Electronic Engineering
business
Image retrieval
Semantic gap
Semantic matching
Remote sensing
Feature detection (computer vision)
Subjects
Details
- ISSN :
- 15580644 and 01962892
- Volume :
- 51
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Geoscience and Remote Sensing
- Accession number :
- edsair.doi...........e5a680822be06580732d708792f8b1a8