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Volumn 14, Issue 10, 2017, Pages 1795-1799

Boosting the Accuracy of Multispectral Image Pansharpening by Learning a Deep Residual Network

Author keywords

Convolutional neural network; data fusion; pansharpening; remote sensing; residual learning

Indexed keywords

CONVOLUTION; DATA FUSION; DEEP LEARNING; FEATURE EXTRACTION; IMAGE FUSION; LEARNING SYSTEMS; NEURAL NETWORKS; PERSONNEL TRAINING; REMOTE SENSING; SPECTRUM ANALYSIS;

EID: 85028507222     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2017.2736020     Document Type: Article
Times cited : (449)

References (24)
  • 2
    • 78650891876 scopus 로고    scopus 로고
    • A new adaptive component-substitutionbased satellite image fusion by using partial replacement
    • Jan.
    • J. Choi, K. Yu, Y. Kim, "A new adaptive component-substitutionbased satellite image fusion by using partial replacement, " IEEE Trans. Geosci. Remote Sens., vol. 49, no. 1, pp. 295-309, Jan. 2011.
    • (2011) IEEE Trans. Geosci. Remote Sens. , vol.49 , Issue.1 , pp. 295-309
    • Choi, J.1    Yu, K.2    Kim, Y.3
  • 4
    • 0034521444 scopus 로고    scopus 로고
    • Smoothing filter-based intensity modulation: A spectral preserve image fusion technique for improving spatial details
    • Dec.
    • J. G. Liu, "Smoothing filter-based intensity modulation: A spectral preserve image fusion technique for improving spatial details, " Int. J. Remote Sens., vol. 21, no. 18, pp. 3461-3472, Dec. 2000.
    • (2000) Int. J. Remote Sens. , vol.21 , Issue.18 , pp. 3461-3472
    • Liu, J.G.1
  • 5
    • 85026995377 scopus 로고    scopus 로고
    • An integrated framework for the spatio-temporal-spectral fusion of remote sensing images
    • Dec.
    • H. Shen, X. Meng, L. Zhang, "An integrated framework for the spatio-temporal-spectral fusion of remote sensing images, " IEEE Trans. Geosci. Remote Sens., vol. 54, no. 12, pp. 7135-7148, Dec. 2016.
    • (2016) IEEE Trans. Geosci. Remote Sens. , vol.54 , Issue.12 , pp. 7135-7148
    • Shen, H.1    Meng, X.2    Zhang, L.3
  • 8
    • 84958974360 scopus 로고    scopus 로고
    • Area-to-point regression kriging for pan-sharpening
    • Apr.
    • Q. Wang, W. Shi, P. M. Atkinson, "Area-to-point regression kriging for pan-sharpening, " ISPRS J. Photogramm. Remote Sens., vol. 114, pp. 151-165, Apr. 2016.
    • (2016) ISPRS J. Photogramm. Remote Sens. , vol.114 , pp. 151-165
    • Wang, Q.1    Shi, W.2    Atkinson, P.M.3
  • 9
    • 84986325587 scopus 로고    scopus 로고
    • Accurate image super-resolution using very deep convolutional networks
    • Las Vegas, NV, USA, Jun.
    • J. Kim, J. K. Lee, K. M. Lee, "Accurate image super-resolution using very deep convolutional networks, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Las Vegas, NV, USA, Jun. 2016, pp. 1646-1654.
    • (2016) Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR) , pp. 1646-1654
    • Kim, J.1    Lee, J.K.2    Lee, K.M.3
  • 10
    • 84962128851 scopus 로고    scopus 로고
    • Image super-resolution using deep convolutional networks
    • Feb.
    • C. Dong, C. C. Loy, K. He, X. Tang, "Image super-resolution using deep convolutional networks, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 38, no. 2, pp. 295-307, Feb. 2016.
    • (2016) IEEE Trans. Pattern Anal. Mach. Intell. , vol.38 , Issue.2 , pp. 295-307
    • Dong, C.1    Loy, C.C.2    He, K.3    Tang, X.4
  • 11
    • 85027937409 scopus 로고    scopus 로고
    • A new pan-sharpening method with deep neural networks
    • May
    • W. Huang, L. Xiao, Z. Wei, H. Liu, S. Tang, "A new pan-sharpening method with deep neural networks, " IEEE Geosci. Remote Sens. Lett., vol. 12, no. 5, pp. 1037-1041, May 2015.
    • (2015) IEEE Geosci. Remote Sens. Lett. , vol.12 , Issue.5 , pp. 1037-1041
    • Huang, W.1    Xiao, L.2    Wei, Z.3    Liu, H.4    Tang, S.5
  • 12
    • 84993982662 scopus 로고    scopus 로고
    • Pansharpening by convolutional neural networks
    • Jul.
    • G. Masi, D. Cozzolino, L. Verdoliva, G. Scarpa, "Pansharpening by convolutional neural networks, " Remote Sens., vol. 8, no. 7, p. 594, Jul. 2016.
    • (2016) Remote Sens. , vol.8 , Issue.7 , pp. 594
    • Masi, G.1    Cozzolino, D.2    Verdoliva, L.3    Scarpa, G.4
  • 14
    • 85021724055 scopus 로고    scopus 로고
    • Beyond a Gaussian denoiser: Residual learning of deep CNN for image denoising
    • Jul.
    • K. Zhang, W. Zuo, Y. Chen, D. Meng, L. Zhang, "Beyond a Gaussian denoiser: Residual learning of deep CNN for image denoising, " IEEE Trans. Image Process., vol. 26, no. 7, pp. 3142-3155, Jul. 2017.
    • (2017) IEEE Trans. Image Process. , vol.26 , Issue.7 , pp. 3142-3155
    • Zhang, K.1    Zuo, W.2    Chen, Y.3    Meng, D.4    Zhang, L.5
  • 15
    • 50549197532 scopus 로고
    • Some methods of speeding up the convergence of iteration methods
    • B. T. Polyak, "Some methods of speeding up the convergence of iteration methods, " USSR Comput. Math. Math. Phys., vol. 4, no. 5, pp. 1-17, 1964.
    • (1964) USSR Comput. Math. Math. Phys. , vol.4 , Issue.5 , pp. 1-17
    • Polyak, B.T.1
  • 16
    • 84913580146 scopus 로고    scopus 로고
    • Caffe: Convolutional architecture for fast feature embedding
    • Y. Jia et al., "Caffe: Convolutional architecture for fast feature embedding, " in Proc. 22nd ACM Int. Conf. Multimedia, 2014, pp. 675-678.
    • (2014) Proc. 22nd ACM Int. Conf. Multimedia , pp. 675-678
    • Jia, Y.1
  • 17
    • 85031032361 scopus 로고    scopus 로고
    • MatConvNet: CNNs for MATLAB. [Online]. Available
    • MatConvNet: CNNs for MATLAB. [Online]. Available: Http://www. vlfeat.org/matconvnet
  • 18
    • 27844607355 scopus 로고    scopus 로고
    • Introduction of sensor spectral response into image fusion methods. Application to wavelet-based methods
    • Oct.
    • X. Otazu, M. Gonzalez-Audicana, O. Fors, J. Nunez, "Introduction of sensor spectral response into image fusion methods. Application to wavelet-based methods, " IEEE Trans. Geosci. Remote Sens., vol. 43, no. 10, pp. 2376-2385, Oct. 2005.
    • (2005) IEEE Trans. Geosci. Remote Sens. , vol.43 , Issue.10 , pp. 2376-2385
    • Otazu, X.1    Gonzalez-Audicana, M.2    Fors, O.3    Nunez, J.4
  • 19
    • 84908077812 scopus 로고    scopus 로고
    • Integrated fusion of multi-scale polar-orbiting and geostationary satellite observations for the mapping of high spatial and temporal resolution land surface temperature
    • Jan.
    • P. H. Wu, H. F. Shen, L. P. Zhang, F. M. Göttsche, "Integrated fusion of multi-scale polar-orbiting and geostationary satellite observations for the mapping of high spatial and temporal resolution land surface temperature, " Remote Sens. Environ., vol. 156, pp. 169-181, Jan. 2015.
    • (2015) Remote Sens. Environ. , vol.156 , pp. 169-181
    • Wu, P.H.1    Shen, H.F.2    Zhang, L.P.3    Göttsche, F.M.4
  • 20
    • 78649286493 scopus 로고    scopus 로고
    • Adaptive multiple-frame image super-resolution based on U-curve
    • Dec.
    • Q. Yuan, L. Zhang, H. Shen, P. Li, "Adaptive multiple-frame image super-resolution based on U-curve, " IEEE Trans. Image Process., vol. 19, no. 12, pp. 3157-3170, Dec. 2010.
    • (2010) IEEE Trans. Image Process. , vol.19 , Issue.12 , pp. 3157-3170
    • Yuan, Q.1    Zhang, L.2    Shen, H.3    Li, P.4
  • 21
    • 84973523368 scopus 로고    scopus 로고
    • Noise removal from hyperspectral image with joint spectral-spatial distributed sparse representation
    • Sep.
    • J. Li, Q. Yuan, H. Shen, L. Zhang, "Noise removal from hyperspectral image with joint spectral-spatial distributed sparse representation, " IEEE Trans. Geosci Remote Sens., vol. 54, no. 9, pp. 5425-5439, Sep. 2016.
    • (2016) IEEE Trans. Geosci Remote Sens. , vol.54 , Issue.9 , pp. 5425-5439
    • Li, J.1    Yuan, Q.2    Shen, H.3    Zhang, L.4
  • 22
    • 85027929099 scopus 로고    scopus 로고
    • Unsupervised feature learning via spectral clustering of multidimensional patches for remotely sensed scene classification
    • May
    • F. Hu, G.-S. Xia, Z. Wang, X. Huang, L. Zhang, "Unsupervised feature learning via spectral clustering of multidimensional patches for remotely sensed scene classification, " IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 8, no. 5, pp. 2015-2030, May 2015.
    • (2015) IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. , vol.8 , Issue.5 , pp. 2015-2030
    • Hu, F.1    Xia, G.-S.2    Wang, Z.3    Huang, X.4    Zhang, L.5
  • 23
    • 84977998287 scopus 로고    scopus 로고
    • Salient band selection for hyperspectral image classification via manifold ranking
    • Jun.
    • Q. Wang, J. Lin, Y. Yuan, "Salient band selection for hyperspectral image classification via manifold ranking, " IEEE Trans. Neural Netw. Learn. Syst., vol. 27, no. 6, pp. 1279-1289, Jun. 2016.
    • (2016) IEEE Trans. Neural Netw. Learn. Syst. , vol.27 , Issue.6 , pp. 1279-1289
    • Wang, Q.1    Lin, J.2    Yuan, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.