Infrared and Laser Engineering, Volume. 54, Issue 5, 20240592(2025)
Degradation-aware transformer for blind hyperspectral and multispectral image fusion(back cover paper·invited)
[1] LIU Pengfei, ZHAO Huaici, LI Peixuan. Hyperspectral images reconstruction using adversarial networks from single RGB image[J]. Infrared and Laser Engineering, 49, 20200093(2020).
[2] CHANG C I, LIN C Y et al. Iterative spectral–spatial hyperspectral anomaly detection[J]. IEEE Transactions on Geoscience and Remote Sensing, 61, 5504330(2023).
[7] CHEN Y, ZENG J, HE W et al. Hyperspectral and multispectral image fusion using factor smoothed tensor ring decomposition[J]. IEEE Transactions on Geoscience and Remote Sensing, 60, 5515417(2022).
[8] CAO X, LIAN Y, WANG K et al. Unsupervised hybrid network of transformer and CNN for blind hyperspectral and multispectral image fusion[J]. IEEE Transactions on Geoscience and Remote Sensing, 62, 5507615(2024).
[9] LI J, ZHENG K, GAO L et al. Enhanced deep image prior for unsupervised hyperspectral image super-resolution[J]. IEEE Transactions on Geoscience and Remote Sensing, 63, 1-1(2025).
[10] [10] QU Y, QI H, KWAN C. Unsupervised sparse dirichlet f hyperspectral image superresolution [C]Proc IEEECVF Conf Computer Vision Pattern Recognition (CVPR), 2018: 25112520.
[12] WANG Z, NG M K, MICHALSKI J et al. A self-supervised deep denoiser for hyperspectral and multispectral image fusion[J]. IEEE Transactions on Geoscience and Remote Sensing, 61, 5520414(2023).
[13] ZHANG L, NIE J, WEI W et al. Unsupervised test-time adaptation learning for effective hyperspectral image super-resolution with unknown degeneration[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 16, 5008-5025(2024).
[14] LI J, ZHENG K, LIU W et al. Model-guided coarse-to-fine fusion network for unsupervised hyperspectral image super-resolution[J]. IEEE Geoscience and Remote Sensing Letters, 20, 5508605(2023).
[15] WANG W, FU X, ZENG W et al. Enhanced deep blind hyperspectral image fusion[J]. IEEE Transactions on Neural Networks and Learning Systems, 34, 1513-1523(2021).
[17] LI J, ZHENG K, YAO J et al. Deep unsupervised blind hyperspectral and multispectral data fusion[J]. IEEE Geoscience and Remote Sensing Letters, 19, 6007305(2022).
[18] GAO L, LI J, ZHENG K et al. Enhanced autoencoders with attention-embedded degradation learning for unsupervised hyperspectral image super-resolution[J]. IEEE Transactions on Geoscience and Remote Sensing, 61, 5509417(2023).
[19] LI J, ZHENG K, LI Z et al. X-shaped interactive autoencoders with cross-modality mutual learning for unsupervised hyperspectral image super-resolution[J]. IEEE Transactions on Geoscience and Remote Sensing, 61, 5518317(2023).
[22] SIMÕES M, BIOUCAS-DIAS J, ALMEIDA L B et al. A convex formulation for hyperspectral image superresolution via subspace-based regularization[J]. IEEE Transactions on Geoscience and Remote Sensing, 53, 3373-3388(2015).
[24] YOU T, WU C, BAI W et al. HMF-Former: Spatio-spectral transformer for hyperspectral and multispectral image fusion[J]. IEEE Geoscience and Remote Sensing Letters, 20, 5500505(2023).
[32] CAO X, LIAN Y, LIU Z et al. Universal high spatial resolution hyperspectral imaging using hybrid-resolution image fusion[J]. Optical Engineering, 62, 033107(2023).
[35] HU J, HUANG T, DENG L et al. Fusformer: A transformer-based fusion network for hyperspectral image super-resolution[J]. IEEE Geoscience and Remote Sensing Letters, 19, 6012305(2022).
Get Citation
Copy Citation Text
Xuheng CAO, Xiaopeng HAO, Yusheng LIAN, Xuquan WANG, Xinbin CHENG. Degradation-aware transformer for blind hyperspectral and multispectral image fusion(back cover paper·invited)[J]. Infrared and Laser Engineering, 2025, 54(5): 20240592
Category: Special issue—Hyperspectral technology and applications
Received: Dec. 19, 2024
Accepted: --
Published Online: May. 26, 2025
The Author Email: