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Experimental Results and Analysis of Foggy Image by Single Image Dehazing Techniques


Affiliations
1 Research Scholar, DAV University Jalandhar, India
2 Assistant Professor, DAV University Jalandhar, India
 

Image de-fogging is the extreme significant in image processing. The problem generally arises due to hanging particles in the atmosphere. It causes a lot of scattering of light that gives rise to the blurring and noise creation in the image. Such conditions in image processing are really undesirable as it causes problem in object visibility and gives a whiteness undesirable effect in the image thus formed. This paper focuses on the review of many state of the art image defogging techniques and thus compares them with implementation in MATLAB 2016Ra image processing tool. In the first phase the image density has been calculated which shows the amount of haziness present in the image. In the second phase the image dehazing techniques has been employed. In the third phase, the results have been gathered in terms of the image quality metrics and analysis shows the comparative results of all the techniques. To clearly show the results the density of the output images is again computed that shows the effect of the technique employed on various images.

Keywords

Image Dehazing, Depth Map-Based Dark Channel Prior, Polarization-Based, Image Quality Assessment.
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  • Experimental Results and Analysis of Foggy Image by Single Image Dehazing Techniques

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Authors

Bindu Goyal
Research Scholar, DAV University Jalandhar, India
Vipan Bansal
Assistant Professor, DAV University Jalandhar, India

Abstract


Image de-fogging is the extreme significant in image processing. The problem generally arises due to hanging particles in the atmosphere. It causes a lot of scattering of light that gives rise to the blurring and noise creation in the image. Such conditions in image processing are really undesirable as it causes problem in object visibility and gives a whiteness undesirable effect in the image thus formed. This paper focuses on the review of many state of the art image defogging techniques and thus compares them with implementation in MATLAB 2016Ra image processing tool. In the first phase the image density has been calculated which shows the amount of haziness present in the image. In the second phase the image dehazing techniques has been employed. In the third phase, the results have been gathered in terms of the image quality metrics and analysis shows the comparative results of all the techniques. To clearly show the results the density of the output images is again computed that shows the effect of the technique employed on various images.

Keywords


Image Dehazing, Depth Map-Based Dark Channel Prior, Polarization-Based, Image Quality Assessment.

References