The following publications are possibly variants of this publication:
- Unsupervised Bayesian Subpixel Mapping of Hyperspectral Imagery Based on Band-Weighted Discrete Spectral Mixture Model and Markov Random FieldYujia Chen, Linlin Xu, Yuan Fang 0003, Junhuan Peng, Wenfu Yang, Alexander Wong, David A. Clausi. lgrs, 18(1):162-166, 2021. [doi]
- Multiobjective Subpixel Mapping With Multiple Shifted Hyperspectral ImagesMi Song, Yanfei Zhong, Ailong Ma, Xiong Xu, Liangpei Zhang. tgrs, 58(11):8176-8191, 2020. [doi]
- Unsupervised Transformer Boundary Autoencoder Network for Hyperspectral Image Change DetectionSong Liu, Haiwei Li, Feifei Wang, Junyu Chen, Geng Zhang, Liyao Song, Bingliang Hu. remotesensing, 15(7):1868, April 2023. [doi]
- A Super-Resolution Convolutional-Neural-Network-Based Approach for Subpixel Mapping of Hyperspectral ImagesXiaofeng Ma, Youtang Hong, Yongze Song, Yujia Chen. staeors, 12(12):4930-4939, 2019. [doi]
- Subpixel Land Cover Mapping Based on Dual Processing Paths for Hyperspectral ImagePeng Wang 0030, Gong Zhang, Liguo Wang, Henry Leung, Hui Bi. staeors, 12(6):1835-1848, 2019. [doi]
- A New Genetic Method for Subpixel Mapping Using Hyperspectral ImagesXiaohua Tong, Xiong Xu, Antonio Plaza, Huan Xie, Haiyan Pan, Wen Cao, Dong Lv. staeors, 9(9):4480-4491, 2016. [doi]
- A Hybrid Subpixel Mapping Framework for Hyperspectral Images Using Collaborative RepresentationYifan Zhang, Xiaoqin Xue, Ting Wang, Mingyi He. staeors, 10(11):5073-5086, 2017. [doi]
- A novel subpixel mapping approach based on spectral unmixing for hyperspectral imagesTing Wang, Yifan Zhang, Shaohui Mei. ispacs 2017: 265-269 [doi]
- Subpixel mapping of hyperspectral images with hybrid endmember library and optimized abundancesYifan Zhang, Ting Wang, Renjie He, Mingyi He. apsipa 2017: 237-241 [doi]