Liu, C.J., Cheng, I., Zhang, Y. and Basu, A. (2017) Enhancement of Low Visibility Aerial Images Using Histogram Truncation and an Explicit Retinex Representation for Balancing Contrast and Color Consistency. Journal of Photogrammetry and Remote Sensing, 128, 16-26.
https://doi.org/10.1016/j.isprsjprs.2017.02.016

has been cited by the following article:

• TITLE: Dehaze Enhancement Algorithm Based on Retinex Theory for Aerial Images Combined with Dark Channel

  AUTHORS: Xinggang Liu, Changjiang Liu, Hengyou Lan, Li Xie

  KEYWORDS: Image Dehazing, Aerial Image, Retinex Algorithm Model, Atmospheric Scattering Model, Dark Channel Dehazing

  JOURNAL NAME: Open Access Library Journal, Vol.7 No.4, April 22, 2020

  ABSTRACT: In order to improve the visual effect of aerial images in foggy weather, a Retinex defogging algorithm combining dark channel priors is proposed to solve the phenomenon of insufficient defogging and over-enhancement of aerial defogging in Reinex defogging. First, the foggy original image is decomposed into foggy incident light components and foggy reflected light components by Retinex theory. Then, the principle of foggy image degradation is analyzed by an atmospheric scattering model, and the dark channel prior defogging algorithm is used to obtain the incident light component and reflected light component after defogging. Finally, a fog-free image was restored through the Reitnex model. The effectiveness of this algorithm is verified through experiments. By comparing and analyzing this algorithm with other defogging algorithms, this algorithm has higher contrast and color fidelity.