ENHANCING THE QUALITY OF HIGHLY HAZED IMAGE USING COLOR ATTENUATION PRIOR AND FUZZY LOGIC
DEEPIKA INGLE
, YOGESH RATHORE
Air light, Image Dehazing, Contrast enhancement, Dark channel prior, Fuzzy Logic, transmission
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.
"ENHANCING THE QUALITY OF HIGHLY HAZED IMAGE USING COLOR ATTENUATION PRIOR AND FUZZY LOGIC", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.2, Issue 6, page no.17-29, July-2017, Available :https://ijnrd.org/papers/IJNRD1707004.pdf
Volume 2
Issue 6,
July-2017
Pages : 17-29
Paper Reg. ID: IJNRD_170104
Published Paper Id: IJNRD1707004
Downloads: 000118816
Research Area: Engineering
Country: raipur, CHHATTISGARH, India
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
Publisher: IJNRD (IJ Publication) Janvi Wave
