Single image fog removal based on local extrema

Abstract

Atmospheric conditions induced by suspended particles, such as fog and haze, severely alter the scene appearance. In this paper, we propose a novel defogging method based on the local extrema, aiming at improving the image visibility under foggy or hazy weather condition. The proposed method utilizes atmospheric scattering model to realize the fog removal. It applies the local extrema method to figure out three pyramid levels to estimate atmospheric veil, and manipulates the tone and contrast of details at different scales through multi-scale tone manipulation algorithm. The results on the experiments of comparison with traditional methods demonstrate that the proposed method can achieve more accurate restoration for the color and details, resulting in a great improvement in image visibility.

Atmospheric Light Estimation Using Polarization Degree Gradient for Image Dehazing

“…The accurate estimation of atmospheric light values is crucial as it influences the projection function's outcome, affecting image realism and potentially causing color distortion. The importance of precise atmospheric light value estimation in the defogging process is highlighted by the potential color distortion in resulting images [6][7][8][9][10].…”

Aerial image defogging method based on nonlocal feature structure tensor by UAV cameras with three-channel RGB cameras

“…19 To reduce the effect of least artifacts, Fu et al 20 used the dark channel prior theory to improve the image restoration process. Zhao et al 21 designed a multiscale enhancement technique to effectively estimate the transmission image. Riaz et al 22 improved the dark channel through block-and pixel-level processing and used an edge-preserving smoothing to reduce the prior failure probability of the dark channel; however, it may introduce halo and gradient inversion effects.…”