Single Image Haze Removal from Image Enhancement Perspective for Real-Time Vision-Based Systems

Vision-based systems operating outdoors are significantly affected by weather conditions, notably those related to atmospheric turbidity. Accordingly, haze removal algorithms, actively being researched over the last decade, have come into use as a pre-processing step. Although numerous approaches ha...

Full description

Saved in:
Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2020-09, Vol.20 (18), p.5170
Main Authors: Ngo, Dat, Lee, Seungmin, Nguyen, Quoc-Hieu, Ngo, Tri Minh, Lee, Gi-Dong, Kang, Bongsoon
Format: Article
Language:English
Subjects:
adaptive tone remapping
Algorithms
Atmospheric aerosols
Computer vision
detail enhancement
field programmable gate array
Field programmable gate arrays
Frames per second
Haze
haze removal
Image enhancement
Image processing
Light
Methods
multiple-exposure image fusion
Real time
real-time processing
Researchers
Source code
Turbidity
Vision systems
Weather
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Vision-based systems operating outdoors are significantly affected by weather conditions, notably those related to atmospheric turbidity. Accordingly, haze removal algorithms, actively being researched over the last decade, have come into use as a pre-processing step. Although numerous approaches have existed previously, an efficient method coupled with fast implementation is still in great demand. This paper proposes a single image haze removal algorithm with a corresponding hardware implementation for facilitating real-time processing. Contrary to methods that invert the physical model describing the formation of hazy images, the proposed approach mainly exploits computationally efficient image processing techniques such as detail enhancement, multiple-exposure image fusion, and adaptive tone remapping. Therefore, it possesses low computational complexity while achieving good performance compared to other state-of-the-art methods. Moreover, the low computational cost also brings about a compact hardware implementation capable of handling high-quality videos at an acceptable rate, that is, greater than 25 frames per second, as verified with a Field Programmable Gate Array chip. The software source code and datasets are available online for public use.
ISSN:1424-8220
1424-8220
DOI:10.3390/s20185170