IJNRD Research Journal

WhatsApp
Click Here

WhatsApp editor@ijnrd.org
IJNRD
INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

Call For Paper

For Authors

Forms / Download

Published Issue Details

Editorial Board

Other IMP Links

Facts & Figure

Impact Factor : 8.76

Issue per Year : 12

Volume Published : 8

Issue Published : 88

Article Submitted : 26375

Article Published : 7533

Total Authors : 19032

Total Reviewer : 980

Total Countries : 150

Indexing Partner

Join RMS/Earn 300

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: ENHANCING THE QUALITY OF HIGHLY HAZED IMAGE USING COLOR ATTENUATION PRIOR AND FUZZY LOGIC
Authors Name: DEEPIKA INGLE , YOGESH RATHORE
Download E-Certificate: Download
Author Reg. ID:
IJNRD_170104
Published Paper Id: IJNRD1707004
Published In: Volume 2 Issue 6, July-2017
DOI:
Abstract: This paper presents fuzzy logic and color attenuation prior based models for remove haze of an image. By creating a linear model for modelling the scene depth of the hazy image under this novel prior and learning the parameters of the model with a supervised learning method, the depth information can be well recovered. The result of that is used as the input of fuzzy logic. This paper presents the design of the technique using fuzzy inference system for contrast enhancement. The aim is to remove haze from a hazy image and it can be achieving by generate an image of higher contrast than the original image by giving a larger weight to the gray levels that are closer to the mean gray level of the image. This approach is applicable to a dehaze image of all type. Experimental results confirm that our method is very effective for both efficiency and the dehazing effect while preserving the small and sharp details in the image.
Keywords: Air light, Image Dehazing, Contrast enhancement, Dark channel prior, Fuzzy Logic, transmission
Cite Article: "ENHANCING THE QUALITY OF HIGHLY HAZED IMAGE USING COLOR ATTENUATION PRIOR AND FUZZY LOGIC", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.2, Issue 6, page no.17-29, July-2017, Available :http://www.ijnrd.org/papers/IJNRD1707004.pdf
Downloads: 000114667
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID:IJNRD1707004
Registration ID: 170104
Published In: Volume 2 Issue 6, July-2017
DOI (Digital Object Identifier):
Page No: 17-29
Country: raipur, CHHATTISGARH, India
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD1707004
Published Paper PDF: https://www.ijnrd.org/papers/IJNRD1707004
Share Article:
Share

Click Here to Download This Article

Article Preview
Click Here to Download This Article

Major Indexing from www.ijnrd.org
Semantic Scholar Microsaoft Academic ORCID Zenodo
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX PUBLON
DRJI SSRN Scribd DocStoc

ISSN Details

ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)


Providing A digital object identifier by DOI
How to Get DOI? DOI

Conference

Open Access License Policy

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Creative Commons License This material is Open Knowledge This material is Open Data This material is Open Content

Important Details

Social Media

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Join RMS/Earn 300

IJNRD