Application of bilateral fusion model based on CNN in hyperspectral image classification
Aiming at the issues of decreasing spatial resolution and feature loss caused by pooling operation in depth CNN-based hyperspectral image classification algorithm,a bilateral fusion block network （DFBN）composed of bilateral fusion blocks was designed.The upper structure of bilateral fusion block was...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2020-11-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020238/ |
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| _version_ | 1841539312624074752 |
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| author | Hongmin GAO Xueying CAO Yao YANG Zaijun HUA Chenming LI |
| author_facet | Hongmin GAO Xueying CAO Yao YANG Zaijun HUA Chenming LI |
| author_sort | Hongmin GAO |
| collection | DOAJ |
| description | Aiming at the issues of decreasing spatial resolution and feature loss caused by pooling operation in depth CNN-based hyperspectral image classification algorithm,a bilateral fusion block network （DFBN）composed of bilateral fusion blocks was designed.The upper structure of bilateral fusion block was constituted by 1×1 convolution and hyperlink,which was used to transfer local spatial characteristics.The lower structure was constituted by pooling layer,convolutional layer,deconvolution layer and upsampling to enhance the characteristics of efficient discrimination.Experimental results on three benchmark hyperspectral image data sets illustrate that the model is superior to other similar classification models. |
| format | Article |
| id | doaj-art-d662453bbb3341bf9b6d67d945f5160e |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2020-11-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-d662453bbb3341bf9b6d67d945f5160e2025-01-14T07:21:09ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2020-11-014113214059738643Application of bilateral fusion model based on CNN in hyperspectral image classificationHongmin GAOXueying CAOYao YANGZaijun HUAChenming LIAiming at the issues of decreasing spatial resolution and feature loss caused by pooling operation in depth CNN-based hyperspectral image classification algorithm,a bilateral fusion block network （DFBN）composed of bilateral fusion blocks was designed.The upper structure of bilateral fusion block was constituted by 1×1 convolution and hyperlink,which was used to transfer local spatial characteristics.The lower structure was constituted by pooling layer,convolutional layer,deconvolution layer and upsampling to enhance the characteristics of efficient discrimination.Experimental results on three benchmark hyperspectral image data sets illustrate that the model is superior to other similar classification models.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020238/convolutional neural networkhyperspectral images classificationtranspose-convolutionupsampling,hyperlink |
| spellingShingle | Hongmin GAO Xueying CAO Yao YANG Zaijun HUA Chenming LI Application of bilateral fusion model based on CNN in hyperspectral image classification Tongxin xuebao convolutional neural network hyperspectral images classification transpose-convolution upsampling,hyperlink |
| title | Application of bilateral fusion model based on CNN in hyperspectral image classification |
| title_full | Application of bilateral fusion model based on CNN in hyperspectral image classification |
| title_fullStr | Application of bilateral fusion model based on CNN in hyperspectral image classification |
| title_full_unstemmed | Application of bilateral fusion model based on CNN in hyperspectral image classification |
| title_short | Application of bilateral fusion model based on CNN in hyperspectral image classification |
| title_sort | application of bilateral fusion model based on cnn in hyperspectral image classification |
| topic | convolutional neural network hyperspectral images classification transpose-convolution upsampling,hyperlink |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020238/ |
| work_keys_str_mv | AT hongmingao applicationofbilateralfusionmodelbasedoncnninhyperspectralimageclassification AT xueyingcao applicationofbilateralfusionmodelbasedoncnninhyperspectralimageclassification AT yaoyang applicationofbilateralfusionmodelbasedoncnninhyperspectralimageclassification AT zaijunhua applicationofbilateralfusionmodelbasedoncnninhyperspectralimageclassification AT chenmingli applicationofbilateralfusionmodelbasedoncnninhyperspectralimageclassification |