research-article

A new single image dehazing method with MSRCR algorithm

Authors:

JinBao Wang,

Ning He,

Ke LuAuthors Info & Claims

ICIMCS '15: Proceedings of the 7th International Conference on Internet Multimedia Computing and Service

Article No.: 19, Pages 1 - 4

https://doi.org/10.1145/2808492.2808511

Published: 19 August 2015 Publication History

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Abstract

In this paper, we propose a new single image dehazing method using a Multi-Scale Retinex with Color Restoration algorithm. The overall dehazing process involves three parts, the atmospheric light value calculation, transmission map estimation, and optimization after dehazing. In addition to a subjective evaluation, image quality was also evaluated objectively using two indicators, Average Gradient, and Information Entropy, in order to consider the detail of the image texture, and image dynamic range. The experimental results show that our algorithm can effectively improve the image quality degraded by foggy weather, is fast, and can retain image details effectively.

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Xia KHu JWang ZWang ZHuang ZLiang Z(2024)Vision-Based Algorithm for Precise Traffic Sign and Lane Line Matching in Multi-Lane ScenariosElectronics10.3390/electronics1314277313:14(2773)Online publication date: 15-Jul-2024
https://doi.org/10.3390/electronics13142773
Fan ZTang CShen YXu MLei Z(2022)RME: a low-light image enhancement model based on reflectance map enhancingSignal, Image and Video Processing10.1007/s11760-022-02358-117:4(1493-1502)Online publication date: 16-Sep-2022
https://doi.org/10.1007/s11760-022-02358-1
Li XHua ZLi J(2022)Color layers -Based progressive network for Single image dehazingMultimedia Tools and Applications10.1007/s11042-022-12731-481:23(32755-32778)Online publication date: 14-Apr-2022
https://doi.org/10.1007/s11042-022-12731-4
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Index Terms

A new single image dehazing method with MSRCR algorithm
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Computer graphics
    1. Image manipulation

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Published In

ICIMCS '15: Proceedings of the 7th International Conference on Internet Multimedia Computing and Service

August 2015

397 pages

ISBN:9781450335287

DOI:10.1145/2808492

General Chairs:
Ramesh Jain
University of California, Irvine
,
Shuqiang Jiang
Institute of Computing Technology, Chinese Academy of Sciences, China
,
Program Chairs:
John Smith
IBM Thomas J. Watson Research Center
,
Jitao Sang
Institute of Automation, Chinese Academy of Sciences, China
,
Guohui Li
National University of Defense Technology, China

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 August 2015

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ICIMCS '15

ICIMCS '15: International Conference on Internet Multimedia Computing and Service

August 19 - 21, 2015

Hunan, Zhangjiajie, China

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ICIMCS '15 Paper Acceptance Rate 20 of 128 submissions, 16%;

Overall Acceptance Rate 163 of 456 submissions, 36%

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Cited By

View all

Xia KHu JWang ZWang ZHuang ZLiang Z(2024)Vision-Based Algorithm for Precise Traffic Sign and Lane Line Matching in Multi-Lane ScenariosElectronics10.3390/electronics1314277313:14(2773)Online publication date: 15-Jul-2024
https://doi.org/10.3390/electronics13142773
Fan ZTang CShen YXu MLei Z(2022)RME: a low-light image enhancement model based on reflectance map enhancingSignal, Image and Video Processing10.1007/s11760-022-02358-117:4(1493-1502)Online publication date: 16-Sep-2022
https://doi.org/10.1007/s11760-022-02358-1
Li XHua ZLi J(2022)Color layers -Based progressive network for Single image dehazingMultimedia Tools and Applications10.1007/s11042-022-12731-481:23(32755-32778)Online publication date: 14-Apr-2022
https://doi.org/10.1007/s11042-022-12731-4
Li PTian JTang YWang GWu C(2021)Deep Retinex Network for Single Image DehazingIEEE Transactions on Image Processing10.1109/TIP.2020.304007530(1100-1115)Online publication date: 2021
https://doi.org/10.1109/TIP.2020.3040075
Harish Babu GVenkatram N(2020)A Survey on Analysis and Implementation of State-of-the-art Haze Removal TechniquesJournal of Visual Communication and Image Representation10.1016/j.jvcir.2020.102912(102912)Online publication date: Sep-2020
https://doi.org/10.1016/j.jvcir.2020.102912
Horani MRawashdeh O(2019)A Framework for Vision-Based Lane Line Detection in Adverse Weather Conditions Using Vehicle-to-Infrastructure (V2I) CommunicationSAE Technical Paper Series10.4271/2019-01-0684Online publication date: 2-Apr-2019
https://doi.org/10.4271/2019-01-0684
Zotin A(2018)Fast Algorithm of Image Enhancement based on Multi-Scale RetinexProcedia Computer Science10.1016/j.procs.2018.04.179131:C(6-14)Online publication date: 1-May-2018
https://dl.acm.org/doi/10.1016/j.procs.2018.04.179
Singh DKumar V(2018)A Comprehensive Review of Computational Dehazing TechniquesArchives of Computational Methods in Engineering10.1007/s11831-018-9294-zOnline publication date: 18-Sep-2018
https://doi.org/10.1007/s11831-018-9294-z

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