A Sea Fog Image Defogging Method Based on the Improved Convex Optimization Model Articles uri icon

authors

  • HUANG, HE
  • LI, ZHANYI
  • NIU, MINGBO
  • MIAH, MD SIPON
  • GAO, TAO
  • WANG, HUIFENG

publication date

  • September 2023

issue

  • 9

volume

  • 11

International Standard Serial Number (ISSN)

  • 2077-1312

abstract

  • Due to the high fog concentration in sea fog images, serious loss of image details is an
    existing problem, which reduces the reliability of aerial visual-based sensing platforms such as
    unmanned aerial vehicles. Moreover, the reflection of water surface and spray can easily lead to
    overexposure of images, and the assumed prior conditions contained in the traditional fog removal
    method are not completely valid, which affects the restoration effectiveness. In this paper, we
    propose a sea fog removal method based on the improved convex optimization model, and realize
    the restoration of images by using fewer prior conditions than that in traditional methods. Compared
    with dark channel methods, the solution of atmospheric light estimation is simplified, and the value
    channel in hue–saturation–value space is used for fusion atmospheric light map estimation. We
    construct the atmospheric scattering model as an improved convex optimization model so that the
    relationship between the transmittance and a clear image is deduced without any prior conditions. In
    addition, an improved split-Bregman iterative method is designed to obtain the transmittance and a
    clear image. Our experiments demonstrate that the proposed method can effectively defog sea fog
    images. Compared with similar methods in the literature, our proposed method can actively extract
    image details more effectively, enrich image color and restore image maritime targets more clearly.
    At the same time, objective metric indicators such as information entropy, average gradient, and the
    fog-aware density evaluator are significantly improved

keywords

  • atmospheric light map; convex optimization; image defogging; iteration; sea fog