Convolutional Neural Networks Based Hyperspectral Image Classification Method with Adaptive Kernels
AbstractHyperspectral image (HSI) classification aims at assigning each pixel a pre-defined class label, which underpins lots of vision related applications, such as remote sensing, mineral exploration and ground object identification, etc. Lots of classification methods thus have been proposed for better hyperspectral imagery interpretation. Witnessing the success of convolutional neural networks (CNNs) in the traditional images based classification tasks, plenty of efforts have been made to leverage CNNs to improve HSI classification. An advanced CNNs architecture uses the kernels generated from the clustering method, such as a K-means network uses K-means to generate the kernels. However, the above methods are often obtained heuristically (e.g., the number of kernels should be assigned manually), and how to data-adaptively determine the number of convolutional kernels (i.e., filters), and thus generate the kernels that better represent the data, are seldom studied in existing CNNs based HSI classification methods. In this study, we propose a new CNNs based HSI classification method where the convolutional kernels can be automatically learned from the data through clustering without knowing the cluster number. With those data-adaptive kernels, the proposed CNNs method achieves better classification results. Experimental results from the datasets demonstrate the effectiveness of the proposed method. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Ding, C.; Li, Y.; Xia, Y.; Wei, W.; Zhang, L.; Zhang, Y. Convolutional Neural Networks Based Hyperspectral Image Classification Method with Adaptive Kernels. Remote Sens. 2017, 9, 618.
Ding C, Li Y, Xia Y, Wei W, Zhang L, Zhang Y. Convolutional Neural Networks Based Hyperspectral Image Classification Method with Adaptive Kernels. Remote Sensing. 2017; 9(6):618.Chicago/Turabian Style
Ding, Chen; Li, Ying; Xia, Yong; Wei, Wei; Zhang, Lei; Zhang, Yanning. 2017. "Convolutional Neural Networks Based Hyperspectral Image Classification Method with Adaptive Kernels." Remote Sens. 9, no. 6: 618.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.