NDLI: Statistical multidirectional line dark channel for single-image dehazing

Content Provider	IET Digital Library
Author	Colores, Sebastián Salazar Sánchez, Eduardo Ulises Moya Arreguín, Juan Manuel Ramos Yépez, Eduardo Cabal
Abstract	Outdoor scenes often contain atmospheric degradation, such as fog or haze, which deteriorate the performance of tracking, autonomous driving and surveillance systems, among others, making dehazing methods an area of considerable interest. However, some dehazing techniques are computationally demanding, generating a trade-off between time-consumption and restoration quality. A new method is proposed for improving outdoor images taken with haze effects while making them less time-consuming. The proposed method was inspired by the Radon transform and tailored for dehazing images by computing the dark channel, in addition to using statistical computations and a heuristic approach to avoid saturated areas. The results obtained were subjected to a reduced-reference image quality dehazing assessment, a full-reference metrics Structural SIMilarity (SSIM) index and peak signal-to-noise ratio (PSNR) over real-world and synthetic outdoor images. The results demonstrate that the proposed method presents an adequate balance between new visible edges, increased gradient and saturated pixels, in addition to obtaining at least a 5% increase in the SSIM index and, a 16% increase in the PSNR index, as well as being 5.37 times faster than the four dehazing methods recently introduced in the literature.
Starting Page	2877
Ending Page	2887
Page Count	11
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 14, Dec (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/14
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.6403
Journal	IET Image Processing
Publisher Date	2019-05-12
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Atmospheric Degradation Autonomous Driving Computer Vision And Image Processing Technique Dehazing Image Dehazing Method Dehazing Technique Fog Full-reference Metrics Structural SIMilarity Index Haze Effect Image Enhancement Image Resolution Image Restoration Optical, Image And Video Signal Processing Outdoor Scenes Radon Transform Radon Transforms Reduced-reference Image Quality Dehazing Assessment Restoration Quality Saturated Areas Single-image Dehazing Statistical Analysis Statistical Computations Statistical Multidirectional Line Dark Channel Statistics Surveillance System Synthetic Outdoor Image
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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