Image Dehazing in Disproportionate Haze Distributions
Journal
IEEE Access
Journal Volume
9
Pages
44599-44609
Date Issued
2021
Author(s)
Abstract
Haze removal techniques employed to increase the visibility level of an image play an important role in many vision-based systems. Several traditional dark channel prior-based methods have been proposed to remove haze formation and thereby enhance the robustness of these systems. However, when the captured images contain disproportionate haze distributions, these methods usually fail to attain effective restoration in the restored image. Specifically, disproportionate haze distribution in an image means that the background region possesses heavy haze density and the foreground region possesses little haze density. This phenomenon usually occurs in a hazy image with a deep depth of field. In response, a novel hybrid transmission map-based haze removal method that specifically targets this situation is proposed in this work to achieve clear visibility restoration and effective information maintenance. Experimental results via both qualitative and quantitative evaluations demonstrate that the proposed method is capable of performing with higher efficacy when compared with other state-of-the-art methods, in respect to both background regions and foreground regions of restored test images captured in real-world environments. ? 2013 IEEE.
Subjects
dark channel prior
disproportionate haze distribution
Haze removal
Demulsification
Restoration
Visibility
Background region
Dark channel priors
Foreground regions
Hybrid transmissions
Quantitative evaluation
Real world environments
State-of-the-art methods
Vision based system
Image reconstruction
SDGs
Type
journal article