Pan-Mamba: Effective pan-sharpening with State Space Model

Schowengerdt, R.A.: Reconstruction of multispatial, multispectral image data using spatial frequency content. Photogrammetric Engineering and Remote Sensing 46

1980

Earlier work this paper cites.

Haydn, R., Dalke, G.W., Henkel, J., Bare, J.E.: Application of the ihs color transform to the processing of multisensor data and image enhancement. National Academy of Sciences of the United States of America 79

1982

Earlier work this paper cites.

Gillespie, A.R., Kahle, A.B., Walker, R.E.: Color enhancement of highly correlated images. ii. channel ratio and "chromaticity" transformation techniques - sciencedirect. Remote Sensing of Environment 22

1987

Earlier work this paper cites.

Yuhas, R.H., Goetz, A.F.H., Boardman, J.W.: Discrimination among semi-arid landscape endmembers using the spectral angle mapper (sam) algorithm (1992), https://api.semanticscholar.org/CorpusID:126879175

1992

Earlier work this paper cites.

Wald, L., Ranchin, T., Mangolini, M.: Fusion of satellite images of different spatial resolutions: Assessing the quality of resulting images. Photogrammetric Engineering and Remote Sensing 63

1997

Earlier work this paper cites.

Nunez, J., Otazu, X., Fors, O., Prades, A., Pala, V., Arbiol, R.: Multiresolution-based image fusion with additive wavelet decomposition. IEEE Transactions on Geoscience and Remote sensing 37

1999

Earlier work this paper cites.

Laben, C., Brower, B.: Process for enhancing the spatial resolution of multispectral imagery using pan-sharpening. US Patent 6011875A (2000)

2000

Earlier work this paper cites.

Liu., J.G.: Smoothing filter-based intensity modulation: A spectral preserve image fusion technique for improving spatial details. International Journal of Remote Sensing 21

2000

Earlier work this paper cites.

Alparone, L., Wald, L., Chanussot, J., Thomas, C., Gamba, P., Bruce, L.M.: Comparison of pansharpening algorithms: Outcome of the 2006 grs-s data fusion contest. IEEE Transactions on Geoscience and Remote Sensing 45

2007

Earlier work this paper cites.

Fasbender, D., Radoux, J., Bogaert, P.: Bayesian data fusion for adaptable image pansharpening. IEEE Transactions on Geoscience and Remote Sensing 46

2008

Earlier work this paper cites.

Dong, C., Loy, C.C., He, K., Tang, X.: Image super-resolution using deep convolutional networks. IEEE Transactions on Pattern Analysis and Machine Intelligence 38

2015

Earlier work this paper cites.

Masi, G., Cozzolino, D., Verdoliva, L., Scarpa, G.: Pansharpening by convolutional neural networks. Remote Sensing 8

2016

Earlier work this paper cites.

Liao, W., Xin, H., Coillie, F.V., Thoonen, G., Philips, W.: Two-stage fusion of thermal hyperspectral and visible rgb image by pca and guided filter. In: Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (2017)

2017

Earlier work this paper cites.

Yang, J., Fu, X., Hu, Y., Huang, Y., Ding, X., Paisley, J.: Pannet: A deep network architecture for pan-sharpening. In: IEEE International Conference on Computer Vision. pp. 5449–5457 (2017)

2017

Earlier work this paper cites.

Yuan, Q., Wei, Y., Meng, X., Shen, H., Zhang, L.: A multiscale and multidepth convolutional neural network for remote sensing imagery pan-sharpening. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11

2018

Cited alongside, same era.

Cai, J., Huang, B.: Super-resolution-guided progressive pansharpening based on a deep convolutional neural network. IEEE Transactions on Geoscience and Remote Sensing 59

2020

Cited alongside, same era.

Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., et al.: An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020)

Original

2020

Cited alongside, same era.

Chen, C.F.R., Fan, Q., Panda, R.: Crossvit: Cross-attention multi-scale vision transformer for image classification. In: Proceedings of the IEEE/CVF international conference on computer vision. pp. 357–366 (2021)

2021

Cited alongside, same era.

Zhou, H., Liu, Q., Wang, Y.: Panformer: A transformer based model for pan-sharpening. In: 2022 IEEE International Conference on Multimedia and Expo (ICME). pp. 1–6. IEEE (2022)

2022

Later among the works it cites.

Zhou, M., Huang, J., Fang, Y., Fu, X., Liu, A.: Pan-sharpening with customized transformer and invertible neural network. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol. 36, pp. 3553–3561 (2022)

2022

Later among the works it cites.

Zhou, M., Huang, J., Yan, K., Yu, H., Fu, X., Liu, A., Wei, X., Zhao, F.: Spatial-frequency domain information integration for pan-sharpening. In: European Conference on Computer Vision. pp. 274–291. Springer (2022)

2022

Later among the works it cites.

Zhou, M., Yan, K., Huang, J., Yang, Z., Fu, X., Zhao, F.: Mutual information-driven pan-sharpening. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 1798–1808 (2022)

2022

Later among the works it cites.