A Variational Gradient-based Fusion Method for Visible and SWIR Imagery

被引:33
作者
Li, Huifang [1 ]
Zhang, Liangpei [1 ]
Shen, Huanfeng [2 ]
Li, Pingxiang [1 ]
机构
[1] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430072, Peoples R China
[2] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China
基金
中国国家自然科学基金;
关键词
ATMOSPHERIC CORRECTION METHODS; LAND-COVER CLASSIFICATION; MULTISPECTRAL IMAGERY; FAST ALGORITHMS; AEROSOL; REFLECTANCE; TRANSFORMATION; EXTRACTION; FEATURES; MODEL;
D O I
10.14358/PERS.78.9.947
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
This paper presents a new variational gradient-based fusion method for visible and short-wave infrared (SWIR) imagery. The proposed method enables spatial enhancement and dehazing of visible imagery. Integrating gradients from SWIR imagery into visible imagery produces a single image with true color and sharp gradients. A constraint based on band correlation is included to improve the enhancement and implement dehazing. The band correlation is according to the quantitative relationship between the wavelength and the atmospheric effect caused by Rayleigh scattering. In this study, both clear and hazy Landsat ETM+ images are used in the experiments. By visual assessment, the gradient of the fused image is more salient than that of the original image, and the true color is well preserved. With the inclusion of the band correlation constraint, the proposed fusion method yields almost haze-free results. Quantitatively, the Metric Q of the fused images is significantly higher than that of the original images; the largest increase of the Metric Q in the experimental results is from 0.0114 to 0.0611. Moreover, for the results of the proposed method, the Metric Q increase in the visible bands declines from blue band to red band.
引用
收藏
页码:947 / 958
页数:12
相关论文
共 39 条
  • [1] Land Cover Classification with Multi-Sensor Fusion of Partly Missing Data
    Aksoy, Selim
    Koperski, Krzysztof
    Tusk, Carsten
    Marchisio, Giovanni
    [J]. PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2009, 75 (05) : 577 - 593
  • [2] [Anonymous], P 4 INT C COMP VIS B
  • [3] A variational model for P+XS image fusion
    Ballester, Coloma
    Caselles, Vicent
    Igual, Laura
    Verdera, Joan
    Rougé, Bernard
    [J]. INTERNATIONAL JOURNAL OF COMPUTER VISION, 2006, 69 (01) : 43 - 58
  • [4] RAYLEIGH-SCATTERING CALCULATIONS FOR THE TERRESTRIAL ATMOSPHERE
    BUCHOLTZ, A
    [J]. APPLIED OPTICS, 1995, 34 (15): : 2765 - 2773
  • [5] Chavez PS, 1996, PHOTOGRAMM ENG REM S, V62, P1025
  • [6] A PHYSICALLY-BASED TRANSFORMATION OF THEMATIC MAPPER DATA - THE TM TASSELED CAP
    CRIST, EP
    CICONE, RC
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1984, 22 (03): : 256 - 263
  • [7] Background-subtraction using contour-based fusion of thermal and visible imagery
    Davis, James W.
    Sharma, Vinay
    [J]. COMPUTER VISION AND IMAGE UNDERSTANDING, 2007, 106 (2-3) : 162 - 182
  • [8] Radiometric Normalization of SPOT-5 Scenes: 6S Atmospheric Model versus Pseudo-invariant Features
    Davranche, Aurelie
    Lefebvre, Gaetan
    Poulin, Brigitte
    [J]. PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2009, 75 (06) : 723 - 728
  • [9] Fast algorithms for removing atmospheric effects from satellite images
    FallahAdl, H
    JaJa, J
    Liang, SL
    Townshend, J
    Kaufman, Y
    [J]. IEEE COMPUTATIONAL SCIENCE & ENGINEERING, 1996, 3 (02): : 66 - 77
  • [10] Fast algorithms for estimating aerosol optical depth and correcting thematic mapper imagery
    Fallah-Adl Hassan
    Jaja Joseph
    Liang Shunlin
    [J]. The Journal of Supercomputing, 1997, 10 (4) : 315 - 329