• Acta Photonica Sinica
  • Vol. 51, Issue 6, 0610005 (2022)
Ming LI, Fan LIU*, and Jingzhi LI
Author Affiliations
  • College of Data Science,Taiyuan University of Technology,Jinzhong,Shanxi 030600,China
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    DOI: 10.3788/gzxb20225106.0610005 Cite this Article
    Ming LI, Fan LIU, Jingzhi LI. Combining Convolutional Attention Module and Convolutional Auto-encoder for Detail Injection Remote Sensing Image Fusion[J]. Acta Photonica Sinica, 2022, 51(6): 0610005 Copy Citation Text show less
    References

    [1] G VIVONE, L ALPARONE, J CHANUSSOT et al. A critical comparison among pansharpening algorithms. IEEE Transactions on Geoscience and Remote Sensing, 53, 2565-2586(2015).

    [2] G VIVONE, M MURA, A GARZELLI et al. new benchmark based on recent advances in multi-spectral pansharpening: revisiting pansharpening with classical and emerging pansharpening methods. IEEE Geoscience and Remote Sensing Magazine, 9, 53-81(2021).

    [3] L YEE, L JUNMIN, Z JIANGSHE. An improved adaptive intensity–hue–saturation method for the fusion of remote sensing images. IEEE Geoscience and Remote Sensing Letters, 11, 985-989(2014).

    [4] S VP, Y NH, K RL. An efficient pan-sharpening method via a combined adaptive PCA approach and contourlets. IEEE Transactions on Geoscience and Remote Sensing, 46, 1323-1335(2008).

    [5] F D JAVAN, F SAMADZADEGAN, S MEHRAVAR et al. review of image fusion techniques for pan-sharpening of high-resolution satellite imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 171, 101-117(2021).

    [6] G VIVONE, R RESTAINO, J CHANUSSOT. A bayesian procedure for full-resolution quality assessment of pansharpened products. IEEE Transactions on Geoscience and Remote Sensing, 56, 4820-4834(2018).

    [7] Xiaopeng PEI. Remote sensing image fusion based on sparse representation(2018).

    [8] C DONG, C C LOY, K HE et al. Image super-resolution using deep convolutional networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38, 295-307(2015).

    [9] F OZCELIK, U ALGANCI, E SERTEL et al. Rethinking CNN-based pansharpening: guided colorization of panchromatic images via GANS. IEEE Transactions on Geoscience and Remote Sensing, 59, 3486-3501(2021).

    [10] Y YANG, H LU, S HUANG et al. An efficient and high-quality pansharpening model based on conditional random fields. Information Sciences, 553, 1-18(2020).

    [11] F RONGRONG, Z JIANGSHE, L JUNMIN et al. Convolutional sparse representation of injected details for pansharpening. IEEE Geoscience and Remote Sensing Letters, 16, 1595-1599(2019).

    [12] H LIN, R YIZHOU, L JUN et al. Pansharpening via detail injection based convolutional neural networks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12, 1188-1204(2019).

    [13] K ITO, K XIONG. Gaussian filters for nonlinear filtering problems. IEEE Transactions on Automatic Control, 45, 910-927(2000).

    [14] M JONATHAN, M UELI, C DAN et al. Stacked convolutional auto-encoders for hierarchical feature extraction, 52-59(2011).

    [15] S WOO, J PARK, J Y LEE et al. Cbam: convolutional block attention module, 3-19(2018).

    [16] J HU, L SHEN, S ALBANIE et al. Squeeze-and-excitation networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42, 2011-2023(2020).

    [17] Fan LIU. Remote sensing image fusion based on wavelet kernel filter and sparse representation(2014).

    [18] S BERA, V K SHRIVASTAVA. Analysis of various optimizers on deep convolutional neural network model in the application of hyperspectral remote sensing image classification. International Journal of Remote Sensing, 41, 2664-2683(2020).

    [19] X MENG, H SHEN, H LI et al. Review of the pansharpening methods for remote sensing images based on the idea of meta-analysis: practical discussion and challenges. Information Fusion, 46, 102-113(2019).

    [20] G VIVONE,, M DALLA, A GARZELLI et al. A benchmarking protocol for pansharpening: dataset, preprocessing, and quality assessment. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 6102-6118(2021).

    [21] Jing ZHANG. Remote sensing image fusion based on sparse representation for detail enhancement(2020).

    [22] Jing ZHANG, Hongtao CHEN, Fan LIU. Remote sensing image fusion based on multivariate empirical mode decomposition and weighted least squares filter. Acta Photonica Sinica, 48, 0510003(2019).

    [23] W ZHOU, A C BOVIK. A universal image quality index. IEEE Signal Processing Letters, 9, 81-84(2002).

    [24] A GARZELLI, F NENCINI, L CAPOBIANCO. Optimal MMSE pan sharpening of very high resolution multispectral images. IEEE Transactions on Geoscience and Remote Sensing, 46, 228-236(2008).

    [25] G MASI, D COZZOLINO, L VERDOLIVA et al. Pansharpening by convolutional neural networks. Remote Sensing, 8, 594(2016).

    [26] A AZARANG, H E MANOOCHEHRI, N KEHTAR NAVAZ. Convolutional autoencoder-based multi-spectral image fusion. IEEE Access, 7, 35673-35683(2019).

    Ming LI, Fan LIU, Jingzhi LI. Combining Convolutional Attention Module and Convolutional Auto-encoder for Detail Injection Remote Sensing Image Fusion[J]. Acta Photonica Sinica, 2022, 51(6): 0610005
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