Optics and Precision Engineering, Volume. 32, Issue 23, 3504(2024)
Specral-spatial classification of hyperspectral imagery with hybrid architecture of 3D-CNN and Transformer
[1] J W YAN, H D CHEN, L LIU. Overview of hyperspectral image classification. Opt. Precision Eng., 27, 680-693(2019).
闫敬文, 陈宏达, 刘蕾. 高光谱图像分类的研究进展. 光学 精密工程, 27, 680-693(2019).
[2] Y LI, H K ZHANG, X Z XUE et al. Deep learning for remote sensing image classification: a survey. WIREs Data Mining and Knowledge Discovery, 8(2018).
[3] D ZHANG, Y Q ZHENG. Hyperspectral remote sensing and its development and application review. Optics & Optoelectronic Technology, 11, 67-73(2013).
张达, 郑玉权. 高光谱遥感的发展与应用. 光学与光电技术, 11, 67-73(2013).
[4] 黄鸿, 郑新磊. 加权空-谱与最近邻分类器相结合的高光谱图像分类. 光学 精密工程, 24, 873-881(2016).
H HUANG, X L ZHENG. Hyperspectral image classification with combination of weighted spatial-spectral and KNN. Opt. Precision Eng., 24, 873-881(2016).
[5] M FAUVEL, Y TARABALKA, J A BENEDIKTSSON et al. Advances in spectral-spatial classification of hyperspectral images. Proceedings of the IEEE, 101, 652-675(2013).
[6] Y S CHEN, H L JIANG, C Y LI et al. Deep feature extraction and classification of hyperspectral images based on convolutional neural networks. IEEE Transactions on Geoscience and Remote Sensing, 54, 6232-6251(2016).
[7] Y LI, H K ZHANG, Q SHEN. Spectral-spatial classification of hyperspectral imagery with 3D convolutional neural network. Remote Sensing, 9, 67(2017).
[8] Z LIU, H Z MAO, C Y WU et al. A ConvNet for the 2020s, 18, 11976-11986(2022).
[9] H K ZHANG, Y LI, Y N JIANG et al. Hyperspectral classification based on lightweight 3-D-CNN with transfer learning. IEEE Transactions on Geoscience and Remote Sensing, 57, 5813-5828(2019).
[10] A DOSOVITSKIY. An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint(2020).
[11] D F HONG, Z HAN, J YAO et al. SpectralFormer: rethinking hyperspectral image classification with transformers. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-15(2022).
[12] S AYAS, E TUNC-GORMUS. SpectralSWIN: a spectral-swin transformer network for hyperspectral image classification. International Journal of Remote Sensing, 43, 4025-4044(2022).
[15] H K ZHANG, W Z HU, X Y WANG.
[16] L SUN, G R ZHAO, Y H ZHENG et al. Spectral-spatial feature tokenization transformer for hyperspectral image classification. IEEE Transactions on Geoscience and Remote Sensing, 60, 3144158(2022).
[17] M BAUMGARDNER, L BIEHL, D LANDGREBE. 220 band AVIRIS hyperspectral image data set: June 12, 1992 Indian pine test site 3. Purdue University Research Repository, 10, 991(2015).
[18] G LICCIARDI, F PACIFICI, D TUIA et al. Decision fusion for the classification of hyperspectral data: outcome of the 2008 GRS-S data fusion contest. IEEE Transactions on Geoscience and Remote Sensing, 47, 3857-3865(2009).
[19] Y F ZHONG, X HU, C LUO et al. WHU-Hi: UAV-borne hyperspectral with high spatial resolution (H2) benchmark datasets and classifier for precise crop identification based on deep convolutional neural network with CRF. Remote Sensing of Environment, 250, 112012(2020).
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Haizhao JING, Lijie TAO, Haokui ZHANG. Specral-spatial classification of hyperspectral imagery with hybrid architecture of 3D-CNN and Transformer[J]. Optics and Precision Engineering, 2024, 32(23): 3504
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Received: Sep. 30, 2024
Accepted: --
Published Online: Mar. 10, 2025
The Author Email: ZHANG Haokui (hkzhang@nwpu.edu.cn)