Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Search and Progressive Image Retrieval from Distributed Image/Video Databases: The SPIRE Project
ECDL '98 Proceedings of the Second European Conference on Research and Advanced Technology for Digital Libraries
Progressive search and retrieval in large image archives
IBM Journal of Research and Development - Papers on mustimedia systems
Comparing global and interest point descriptors for similarity retrieval in remote sensed imagery
Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems
Learning-based license plate detection in vehicle image database
International Journal of Intelligent Information and Database Systems
Adaptive directional wavelet transform based on directional prefiltering
IEEE Transactions on Image Processing
A hierarchical scheme of multiple feature fusion for high-resolution satellite scene categorization
ICVS'13 Proceedings of the 9th international conference on Computer Vision Systems
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In this paper, the performance of similarity retrieval from satellite image databases by using different sets of spatial and transformed-based texture features is evaluated and compared. A benchmark consisting of 37 satellite image clips from various satellite instruments is devised for the experiments. We show that although the proposed feature set perform only slightly better with the Brodatz set, its performance is far superior for the satellite images. The result indicates that more than 25% of the benchmark patterns can be retrieved with more than 80% accuracy by using normalized Euclidean distance. In contrast, less than 10% of the patterns are retrieved with more than 80% accuracy by using transformed-based feature sets (such as those based on Gabor filter or quadrature mirror filter (QMF)).