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首页> 外文期刊>Journal of visual communication & image representation >Residential area extraction based on saliency analysis for high spatial resolution remote sensing images
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Residential area extraction based on saliency analysis for high spatial resolution remote sensing images

机译：基于显着性分析的高空间分辨率遥感影像居民区提取

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Traditional residential area extraction methods for remote sensing image depend on classification, segmentation and prior knowledge which are time-consuming and difficult to build. In this paper, an efficient, saliency analysis-based residential area extraction method is proposed. In the proposed model, an adaptive directional prediction-based lifting wavelet transform (ADP-LWT) is introduced to obtain the orientation feature. A logarithm co-occurrence histogram is employed to compute the intensity feature. The color opponency and diagram objection based on the information are proposed to extract color feature from the contrast in the red-green opponent channel. The saliency map is obtained through a weighted combination based on the feature competition and the residential area is extracted by saliency map threshold segmentation. The experimental results reveal that the residential area extracted by our model has more demarcated boundaries and better performance in background subtraction. (C) 2015 Elsevier Inc. All rights reserved.
机译：传统的用于遥感图像的居住区提取方法取决于分类，分割和先验知识，这些方法既费时又难以构建。本文提出了一种基于显着性分析的高效居民区提取方法。在所提出的模型中，引入了基于自适应方向预测的提升小波变换（ADP-LWT），以获得方向特征。对数共现直方图用于计算强度特征。提出了基于信息的颜色对比例和图表异议，从红绿对手通道的对比度中提取颜色特征。通过基于特征竞争的加权组合获得显着图，并通过显着图阈值分割提取居住区。实验结果表明，我们的模型提取的居民区划定了边界，并且在背景扣除方面表现更好。 （C）2015 Elsevier Inc.保留所有权利。

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