doi:10.16186/j.cnki.1673-9787.2020040002

Received:2020/04/01

Revised:2020/05/18

Published:2021/09/15

Research on image defogging based on sky region segmentation and conditional constraint optimization

LI Shuping, ZHANG Liao, LIU Junli

School of Mechanical and Power Engineering， Henan Polytechnic University， Jiaozuo 454000 ， Henan， China

Abstract:In view of the phenomenon of blurry scene， target loss and poor quality by imaging equipment in foggy environment leading to the decrease of image recognition rate ， an image defogging method was proposed based on sky region segmentation and conditional constraint optimization to solve the problems of halo and distortion in the sky region caused by dark channel prior. After preprocessing the image， the image was divided in-to sky region and non-sky region. The gray histogram was used to estimate the ambient light. The transmittance of the non-sky region was constrained by using known conditions. The method could adaptively increase the transmittance of the sky region， which avoided serious color distortion in the sky region. The transmittance of the two parts were filtered and refined after merging. The experimental results showed that the outlines and de-tails of fog images with sky area were improved greatly after using this algorithm ， capable of satisfying the purpose of defogging well. This was of great significance to improve the working efficiency of imaging equipment in foggy environment.

Key words:sky region segmentation;conditional constraint;image defogging;dark channel prior;transmittances

 基于天空区域分割和条件约束优化的图像去雾研究_李树平.pdf