Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-6, 83-88, 2014
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-6/83/2014/
doi:10.5194/isprsarchives-XL-6-83-2014
© Author(s) 2014. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
23 Apr 2014
Remote Sensing Image Retrieval with Combined Features Of Salient Region
Z. F. Shao1, W. X. Zhou1, and Q. M. Cheng2 1State key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, China
2The Department of Electronics and Information Engineering, Huazhong University of Science & Technology, China
Keywords: Visual Attention Model, Object Saliency, Salient Regions, Combined Features, Remote Sensing Image Retrieval Abstract. Low-level features tend to achieve unsatisfactory retrieval results in remote sensing image retrieval community because of the existence of semantic gap. In order to improve retrieval precision, visual attention model is used to extract salient objects from image according to their saliency. Then color and texture features are extracted from salient objects and regarded as feature vectors for image retrieval. Experimental results demonstrate that our method improves retrieval results and obtains higher precision.
Conference paper (PDF, 769 KB)


Citation: Shao, Z. F., Zhou, W. X., and Cheng, Q. M.: Remote Sensing Image Retrieval with Combined Features Of Salient Region, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-6, 83-88, doi:10.5194/isprsarchives-XL-6-83-2014, 2014.

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