The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XL-6
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-6, 83–88, 2014
https://doi.org/10.5194/isprsarchives-XL-6-83-2014
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-6, 83–88, 2014
https://doi.org/10.5194/isprsarchives-XL-6-83-2014

  23 Apr 2014

23 Apr 2014

Remote Sensing Image Retrieval with Combined Features Of Salient Region

Z. F. Shao1, W. X. Zhou1, and Q. M. Cheng2 Z. F. Shao et al.
  • 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.