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REMOTE SENSING IMAGE RETRIEVAL WITH COMBINED FEATURES OF SALIENT REGION

机译:遥感图像检索突出区域的组合特征

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摘要

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.
机译:由于存在语义差距存在,低级功能往往达到遥感图像检索社区的不令人满意的检索。为了提高检索精度,可视注意模型用于根据其显着性从图像中提取突出对象。然后从突出对象中提取颜色和纹理特征,并视为图像检索的特征向量。实验结果表明,我们的方法改善了检索结果并获得更高的精度。

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