Land-Use Scene Classification in High-Resolution Remote Sensing Images Using Improved Correlatons

Qi Kunlun; Wu Huayi; Shen Chen; Gong Jianya

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Land-Use Scene Classification in High-Resolution Remote Sensing Images Using Improved Correlatons

机译：使用改进的相关性的高分辨率遥感影像中的土地利用场景分类

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Existing methods that incorporate spatial information into a traditional Bag-of-Visual-Words (BoVW) model consider the spatial arrangement of an image but ignore pixel homogeneity in land-use remote sensing images. In this letter, we present an improved correlaton model to jointly integrate appearance, spatial correlation, and pixel homogeneity using multiscale segmentation. The effectiveness of the proposed method was tested on a ground truth image data set of 21 land-use classes manually extracted from high-resolution remote sensing images. The experimental results demonstrate that our improved correlaton model can promote classification and outperforms existing methods such as the traditional BoVW model, spatial pyramid matching model, and the traditional correlaton model.

机译：现有将空间信息合并到传统的视觉单词袋（BoVW）模型中的方法考虑了图像的空间排列，但忽略了土地利用遥感图像中的像素均匀性。在这封信中，我们提出了一种改进的相关子模型，以使用多尺度分割共同整合外观，空间相关性和像素均匀性。在从高分辨率遥感图像中手动提取的21种土地利用类别的地面真实图像数据集上测试了该方法的有效性。实验结果表明，我们改进的相关子模型可以促进分类，并且优于传统的BoVW模型，空间金字塔匹配模型和传统的相关子模型等现有方法。

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《Geoscience and Remote Sensing Letters, IEEE》 |2015年第12期|2403-2407|共5页
作者
Qi Kunlun; Wu Huayi; Shen Chen; Gong Jianya;
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正文语种 eng
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关键词
Bag-of-visual-words (BoVW); correlaton; pixel homogeneity; scene classification; spatial correlation;

机译：视觉词袋（BoVW）;相关性;像素同质性;场景分类;空间相关性;

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专利

1. Scene classification of high-resolution remote sensing images based on IMFNet [J] . Zhang Xin, Wang Yongcheng, Zhang Ning, Journal of Applied Remote Sensing . 2019,第4期

机译：基于IMFNET的高分辨率遥感图像的场景分类
2. Improved Class-Specific Codebook with Two-Step Classification for Scene-Level Classification of High Resolution Remote Sensing Images [J] . Li Yan, Ruixi Zhu, Nan Mo, Remote Sensing . 2017,第3期

机译：改进的具有两步分类的特定于类别的密码本，用于高分辨率遥感影像的场景级分类
3. Improved Class-Specific Codebook with Two-Step Classification for Scene-Level Classification of High Resolution Remote Sensing Images [J] . Li Yan, Ruixi Zhu, Nan Mo, Remote Sensing . 2017,第3期

机译：改进的具有两步分类的特定于类别的密码本，用于高分辨率遥感影像的场景级分类
4. Deep sparse representations for land-use scene classification in remote sensing images [C] . Fan Hu, Gui-Song Xia, Liangpei Zhang International Conference on Automatic Control and Dynamic Optimization Techniques . 2016

机译：遥感图像中土地利用场景分类的深度稀疏表示
5. Development and evaluation of advanced classification systems using remotely sensed data for accurate land-use/land-cover mapping. [D] . Yuan, Hui. 2002

机译：使用遥感数据开发和评估高级分类系统，以进行准确的土地利用/土地覆盖制图。
6. Training Convolutional Neural Networks with Multi-Size Images and Triplet Loss for Remote Sensing Scene Classification [O] . Jianming Zhang, Chaoquan Lu, Jin Wang, 2020

机译：利用多尺寸图像和三重态损失训练卷积神经网络进行遥感场景分类
7. Retraction: Zhu R. et al. Attention-Based Deep Feature Fusion for the Scene Classification of High-Resolution Remote Sensing Images. Remote Sensing. 2019, 11(17), 1996 [O] . Ruixi Zhu, Li Yan, Nan Mo, 2020

机译：撤回：朱R.等。基于关注的高分辨率遥感图像场景分类的深度特征融合。遥感。 2019,11（17），1996年

Land-Use Scene Classification in High-Resolution Remote Sensing Images Using Improved Correlatons

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