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多尺度膨胀卷积神经网络资源三号卫星影像云识别

Cloud Detection Based on Multi-Scale Dilation Convolutional Neural Network for ZY-3 Satellite Remote Sensing Imagery

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摘要

为提高影像云识别精度, 提出一种多尺度膨胀卷积深层神经网络云识别方法。结合卫星影像特征, 设计云识别卷积神经网络结构, 该结构包含深层特征编码模块、局部多尺度膨胀感知模块以及云区预测解码模块。首先, 编码模块中通过基础卷积层获取深度特征; 其次, 联合多尺度膨胀卷积和池化层共同感知, 每层操作连接非线性函数, 以提升网络模型的表达能力; 最后, 云区预测解码模块中融合对应编码模块的特征, 再利用L1正则化上采样算法实现端对端的像素级云识别结果。选用典型云遮挡区域影像进行云识别实验, 并与Otsu算法和FCN-8S算法进行对比。结果表明, 本文所提算法的检测精度较高, Kappa系数显著提升。

Abstract

To improve the accuracy of cloud detection, we propose a multi-scale dilation convolutional neural network method. Combining with the characteristic of satellite images, we design the deep convolution network structure, which includes a deep-feature coding module, a local dilation perception module, and a cloud-dense decoding module. First, the deep-features of cloud are obtained by the basic convolutional layer in conjunction with the coding module. Second, multi-scale dilation convolution layers jointed with pooling layers are used to perceive corporately. A nonlinear function is employed in each block to improve the effectiveness of network model expression. Finally, the cloud-dense decoding module integrate the features corresponding to those included in the coding module and then utilize the L1 regularization upsampling algorithm to accomplish the end-to-end pixel-level cloud detection task. Cloud detection experiments are performed in the typical cloud mask areas; the results are compared with those of the Otsu algorithm and the FCN-8S method. The results indicate that the accuracy of proposed method is higher and the Kappa coefficient is effectively improved.

Newport宣传-MKS新实验室计划
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中图分类号:P237

DOI:10.3788/aos201939.0104002

所属栏目:探测器

基金项目:国家自然科学基金青年基金(61601213)、中国博士后科学基金(2017M611252)、辽宁省公益研究基金计划 (20170003)

收稿日期:2018-08-08

修改稿日期:2018-08-22

网络出版日期:2018-09-10

作者单位    点击查看

高琳:辽宁工程技术大学测绘与地理科学学院, 辽宁 阜新 123000国家测绘地理信息局卫星测绘应用中心, 北京 100048
宋伟东:辽宁工程技术大学测绘与地理科学学院, 辽宁 阜新 123000
谭海:国家测绘地理信息局卫星测绘应用中心, 北京 100048
刘阳:辽宁工程技术大学测绘与地理科学学院, 辽宁 阜新 123000国家测绘地理信息局卫星测绘应用中心, 北京 100048

联系人作者:宋伟东(Lntu_swd@163.com); 高琳(gaolin19920324@163.com);

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引用该论文

Gao Lin,Song Weidong,Tan Hai,Liu Yang. Cloud Detection Based on Multi-Scale Dilation Convolutional Neural Network for ZY-3 Satellite Remote Sensing Imagery[J]. Acta Optica Sinica, 2019, 39(1): 0104002

高琳,宋伟东,谭海,刘阳. 多尺度膨胀卷积神经网络资源三号卫星影像云识别[J]. 光学学报, 2019, 39(1): 0104002

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