Fusion of Hyperspectral and Panchromatic Images Using Improved HySure Method

被引:0
|
作者
Lin, Hongwen [1 ]
Zhang, Anqing [1 ]
机构
[1] Dalian Naval Acad, Dept Informat Combat, Dalian, Peoples R China
关键词
hyperspectral image; fusion; pansharpening; improved HySure method;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Hyperspectral image applications have been explored in various areas, but they are often suffered from coarser spatial resolutions. In recent years, many pan-sharpening approaches which are originally used for fusing panchromatic image with multispectral one have been adapted to hyperspectral images. Most of them ignore the fact that the spectral coverage of the panchromatic image does not match the wavelength acquisition range of the hyperspectal one. In this paper, we proposed an improved HySure method which pays more attention to the bands of hyperspectal image that not covered by panchromatic one. HySure method is used twice in our method. First, it is used to fuse the original observed hyperspectal image with the panchromatic one, and the fusion result is used to construct an intermediate multispectral image which has the same spectral coverage as the hyperspectal one. Then the hyperspectal image and the multispectral one are fused by HySure method again. Experimental results show that improved method is superior to the original one in some image quality measurements, such as cross correlation (CC), root-mean-square error (RMSE), spectral angle mapper (SAM), universal image quality index (UIQI), and relative dimensionless global error in synthesis (ERGAS).
引用
收藏
页码:489 / 493
页数:5
相关论文
共 50 条
  • [41] Fusion of multi-spectral and panchromatic images using fuzzy rule
    Yang, Xu-Hong
    Jing, Zhong-Liang
    Liu, Gang
    Hua, Li-Zhen
    Ma, Da-Wei
    COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2007, 12 (07) : 1334 - 1350
  • [42] FUSION OF PANCHROMATIC AND MULTISPECTRAL IMAGES USING MULTISCALE DUAL BILATERAL FILTER
    Hu, Jianwen
    Li, Shutao
    2011 18TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2011, : 1489 - 1492
  • [43] Fusion of Panchromatic and Multispectral Images Using Multiscale Convolution Sparse Decomposition
    Zhang, Kai
    Zhang, Feng
    Feng, Zhixi
    Sun, Jiande
    Wu, Quanyuan
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2021, 14 : 426 - 439
  • [44] Stepwise Fusion of Hyperspectral, Multispectral and Panchromatic Images with Spectral Grouping Strategy: A Comparative Study Using GF5 and GF1 Images
    Huang, Leping
    Hu, Zhongwen
    Luo, Xin
    Zhang, Qian
    Wang, Jingzhe
    Wu, Guofeng
    REMOTE SENSING, 2022, 14 (04)
  • [45] A new residual fusion classification method for hyperspectral images
    Yang, Jinghui
    Wang, Liguo
    Qian, Jinxi
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2016, 37 (04) : 745 - 769
  • [46] Panchromatic and Hyperspectral Image Fusion: Outcome of the 2022 WHISPERS Hyperspectral Pansharpening Challenge
    Vivone, Gemine
    Garzelli, Andrea
    Xu, Yang
    Liao, Wenzhi
    Chanussot, Jocelyn
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2023, 16 : 166 - 179
  • [47] Fusion and registration of THEOS multispectral and panchromatic images
    Sritarapipat, Tanakorn
    Kasetkasem, Teerasit
    Rakwatin, Preesan
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2014, 35 (13) : 5120 - 5147
  • [48] Multispectral and Panchromatic Images Fusion by Adaptive PCNN
    Li, Yong
    Wang, Ke
    Chen, Da-ke
    ADVANCES IN MULTIMEDIA MODELING, PROCEEDINGS, 2010, 5916 : 120 - 129
  • [49] Fusion of Panchromatic and Multispectral Images by Genetic Algorithms
    Garzelli, Andrea
    Nencini, Filippo
    2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8, 2006, : 3810 - 3813
  • [50] FUSION OF HYPERSPECTRAL AND PANCHROMATIC DATA BY SPECTRAL UNMIXING IN THE REFLECTIVE DOMAIN
    Constans Y.
    Fabre S.
    Brunet H.
    Seymour M.
    Crombez V.
    Chanussot J.
    Briottet X.
    Deville Y.
    Revue Francaise de Photogrammetrie et de Teledetection, 2022, 224 (01): : 59 - 74