Localization of radiance transformation for image dehazing in wavelet domain

Hazy image observation is a serious phenomenon occurred by random scattering of atmospheric elements. This reduces the scene prominence in terms of color contrast and makes the vision system poor. To overcome this issue, dehazing of digital images is dealt with much attention in the field of computer vision. Dense scattering in hazy image results in loss of original spectral information of the object. It is required to remove the unwanted artifacts of weather during image acquisition process of the given object to improve the visual insight of an acquired image. It is found that most of the existing methods fail to retrieve the sufficient information from hazy images. To address such problem, a robust single image dehazing method is introduced to recover the haze-free image. This is performed by calculating the atmospheric light of the given hazy images by decomposing and retaining the high frequency sub bands using wavelet domain. The dense haze elimination is performed on approximated low frequency sub band of the given hazy image. On reconstruction process, well-refined dehaze image is obtained. Moreover, transmission maps are also produced as a byproduct of this method. (C) 2019 Elsevier B.V. All rights reserved.