A Comprehensive Study on Computational Pansharpening Techniques for Remote Sensing Images

被引:24
|
作者
Kaur, Gurpreet [1 ]
Saini, Kamaljit Singh [1 ]
Singh, Dilbag [2 ]
Kaur, Manjit [2 ]
机构
[1] Chandigarh Univ, Gharuan, India
[2] Bennett Univ, Sch Engn & Appl Sci, Greater Noida, India
关键词
PAN-SHARPENING METHOD; LEARNING APPROACH; FUSION; MODEL; CLASSIFICATION; FUZZY; IHS;
D O I
10.1007/s11831-021-09565-y
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Real-time remote sensing imaging systems require high spatial resolution multispectral images. However, the remote sensing images obtained from a single satellite sensor do not provide a significant amount of information. Therefore, pansharpening techniques are desirable to provide high spatial resolution multispectral images. The hyperspectral pansharpening techniques are used to fuse the hyperspectral (HS) and the panchromatic (PAN) images to obtain an HS image with a significant amount of spatial and spectral information. The main objective of this paper is to provide a comprehensive review of the pansharpening techniques. Various categories of pansharpening techniques are also discussed. This paper provides three different summaries: initially, the conceptual aspects of pansharpening techniques are discussed. Thereafter, the comparative analyses are performed to evaluate the benefits and shortcomings of the existing pansharpening techniques. Finally, challenges and opportunities for future research in the field of pansharpening are discussed.
引用
收藏
页码:4961 / 4978
页数:18
相关论文
共 50 条
  • [41] The application of remote sensing techniques to the study of ophiolites
    Khan, Shuhab D.
    Mahmood, Khalid
    EARTH-SCIENCE REVIEWS, 2008, 89 (3-4) : 135 - 143
  • [42] Multi-sensor image fusion for pansharpening in remote sensing
    Ehlers, Manfred
    Klonus, Sascha
    Astrand, Par Johan
    Rosso, Pablo
    INTERNATIONAL JOURNAL OF IMAGE AND DATA FUSION, 2010, 1 (01) : 25 - 45
  • [43] A NOVEL ADAPTIVE REMOTE SENSING PANSHARPENING ALGORITHM BASED ON THE ICM
    Zhao, H. T.
    Li, X. J.
    Li, Y. K.
    Ge, J. F.
    Xu, X. Y.
    URBAN GEOINFORMATICS 2022, 2022, : 97 - 102
  • [44] A Framework for Remote Sensing Images Processing Using Deep Learning Techniques
    Cresson, Remi
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2019, 16 (01) : 25 - 29
  • [45] Interactive Change Detection Techniques in Multitemporal Multispectral Remote Sensing Images
    Alhichri, Haikel
    Bazi, Yakoub
    Alajlan, Naif
    Ahamad, Sayed M.
    2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, : 6173 - 6176
  • [46] Enhanced EDX images by fusion of multimodal SEM images using pansharpening techniques
    Franchi, G.
    Angulo, J.
    Moreaud, M.
    Sorbier, L.
    JOURNAL OF MICROSCOPY, 2018, 269 (01) : 94 - 112
  • [47] A Review on Various Shadow Detection and Compensation Techniques in Remote Sensing Images
    Mostafa, Yasser
    CANADIAN JOURNAL OF REMOTE SENSING, 2017, 43 (06) : 545 - 562
  • [48] DRBOX FAMILY: A GROUP OF OBJECT DETECTION TECHNIQUES FOR REMOTE SENSING IMAGES
    Liu, Lei
    Pan, Zongxu
    Chen, Guowei
    Gao, Yizhao
    2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, : 1446 - 1449
  • [49] MULTICLASS CLASSIFICATION OF REMOTE SENSING IMAGES USING DEEP LEARNING TECHNIQUES
    Arshad, Tahir
    Zhang Junping
    Qingyan Wang
    IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2023, : 7234 - 7237
  • [50] Research on super-resolution reconstruction of remote sensing images: a comprehensive review
    Liu, Hui
    Qian, Yurong
    Zhong, Xiwu
    Chen, Long
    Yang, Guangqi
    OPTICAL ENGINEERING, 2021, 60 (10)