Open AccessDehazing of remote sensing images using fourth‐order partial differential equations based trilateral filter
Author(s) -
Singh Dilbag,
Kumar Vijay
Publication year - 2018
Publication title -
iet computer vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 37
eISSN - 1751-9640
pISSN - 1751-9632
DOI - 10.1049/iet-cvi.2017.0044
Subject(s) - haze , visibility , distortion (music) , computer science , artificial intelligence , computer vision , pixel , remote sensing , filter (signal processing) , image restoration , diffuse sky radiation , image (mathematics) , scattering , image processing , geology , optics , geography , physics , meteorology , telecommunications , amplifier , bandwidth (computing)
Remote sensing images taken in hazy situations are degraded by scattering of atmospheric particles, which greatly influences the efficiency of visual systems. Therefore, the visibility restoration of hazy images becomes a significant area of research. In this study, a fourth‐order partial differential equations based trilateral filter (FPDETF) dehazing approach is proposed to enhance the coarse estimated atmospheric veil. FPDETF is able to reduce halo and gradient reversal artefacts. It also preserves the radiometric information of haze‐free images. The visibility restoration phase is also refined to reduce the colour distortion of dehazed images. The proposed technique has been evaluated on ten well‐known remote sensing images and also compared with seven well‐known existing dehazing approaches. The experimental results reveal that the proposed technique outperforms others in terms of contrast gain and percentage of saturated pixels.