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)
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
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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
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