Image pan-sharpening using enhancement based approaches in remote sensing

被引:7
|
作者
Khan, Sarwar Shah [1 ]
Ran, Qiong [1 ]
Khan, Muzammil [2 ]
机构
[1] Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing 100029, Peoples R China
[2] Univ Swat, Dept Comp & Software Technol, Swat 19130, Pakistan
关键词
Cross-domain; Laplacian filter; Discrete Fourier transform; Pan-sharpening; Matting model; Image enhancement; Multispectral and panchromatic images; TRANSFORM; FUSION;
D O I
10.1007/s11042-020-09682-z
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes to do image enhancement before pan-sharpening; that is, the image enhancement techniques are used as a pre-processing step. The image enhancement techniques are proposed in two domains, same-domain and cross-domain. In the same-domain methods, the image enhancement techniques (such as Laplacian, Unsharp) are simply applied to multispectral (MS) and panchromatic (PAN) images to sharpen both images in the spatial domain. While in cross-domain, a novel hybrid combination of Laplacian Filter (LF) and Discrete Fourier Transformation (DFT) image sharpening technique is introduced. After image enhancement, the powerful Matting Model (MM) pan-sharpening technique is used to fuse both the enhanced images and produce a resultant image with the high spatial and spectral resolutions. The experimental results of the proposed approach outperform the others as compared to the state-of-art techniques over three datasets. The results are evaluated, considering both Qualitative and Quantitative evaluation metrics.
引用
收藏
页码:32791 / 32805
页数:15
相关论文
共 50 条
  • [1] Image pan-sharpening using enhancement based approaches in remote sensing
    Sarwar Shah Khan
    Qiong Ran
    Muzammil Khan
    [J]. Multimedia Tools and Applications, 2020, 79 : 32791 - 32805
  • [2] PAN-SHARPENING APPROACHES BASED ON UNMIXING OF MULTISPECTRAL REMOTE SENSING IMAGERY
    Palubinskas, G.
    [J]. XXIII ISPRS CONGRESS, COMMISSION VII, 2016, 41 (B7): : 693 - 702
  • [3] Pan-sharpening for compressed remote sensing images
    Liu, Yixiao
    Liu, Gang
    Ren, Chao
    Teng, Qizhi
    He, Xiaohai
    [J]. JOURNAL OF APPLIED REMOTE SENSING, 2021, 15 (03)
  • [4] Remote sensing image pan-sharpening via Pixel difference enhance
    Feng, Xiaoxiao
    Wang, Jiaming
    Zhang, Zhiqi
    Chang, Xueli
    [J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2024, 132
  • [5] PSGAN: A GENERATIVE ADVERSARIAL NETWORK FOR REMOTE SENSING IMAGE PAN-SHARPENING
    Liu, Xiangyu
    Wang, Yunhong
    Liu, Qingjie
    [J]. 2018 25TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2018, : 873 - 877
  • [6] Attention-Based Tri-UNet for Remote Sensing Image Pan-Sharpening
    Zhang, Wanwan
    Li, Jinjiang
    Hua, Zhen
    [J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2021, 14 : 3719 - 3732
  • [7] PSGAN: A Generative Adversarial Network for Remote Sensing Image Pan-Sharpening
    Liu, Qingjie
    Zhou, Huanyu
    Xu, Qizhi
    Liu, Xiangyu
    Wang, Yunhong
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2021, 59 (12): : 10227 - 10242
  • [8] DADR: Dual Attention Based Dual Regression Network for Remote Sensing Image Pan-Sharpening
    Su, Xunyang
    Li, Jinjiang
    Hua, Zhen
    [J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2022, 15 : 4397 - 4413
  • [9] Pan-sharpening algorithm for remote sensing images based on local correlation
    Tao, Xu-Ting
    He, Hong-Jie
    Chen, Fan
    Yin, Zhong-Ke
    [J]. Guangzi Xuebao/Acta Photonica Sinica, 2014, 43 (03):
  • [10] Intermodality models in pan-sharpening: analysis based on remote sensing physics
    Zhang, Hankui
    Huang, Bo
    Yu, Le
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2014, 35 (02) : 515 - 531