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DC Field | Value | Language |
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dc.contributor.author | Pal, N.S. | - |
dc.contributor.author | Lal, S. | - |
dc.contributor.author | Shinghal, K. | - |
dc.date.accessioned | 2020-03-31T06:51:19Z | - |
dc.date.available | 2020-03-31T06:51:19Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Engineering Science and Technology, an International Journal, 2019, Vol.22, 1, pp.22-32 | en_US |
dc.identifier.uri | 10.1016/j.jestch.2018.11.006 | - |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/9708 | - |
dc.description.abstract | This paper presents a robust framework for visibility enhancement of images degraded by foggy weather conditions. The proposed defogged algorithm is developed by the combining of modified visibility restoration approach and S-shaped transfer function for foggy weather degraded images. The proposed defogged algorithm works in two steps: in first step trilateral filter based visibility restoration algorithm is used for visibility and smoothness of the degraded images. Further in the second step S-shaped transfer function is used for contrast enhancement of the foggy images. The image quality metrics of proposed defogged and other existing visibility restoration algorithms are evaluated in terms of Fog Reduction Factor (FRF), Measure of Enhancement Factor (EMF) and blind parameter (?) on different foggy image databases. We demonstrate the strength of proposed defogged algorithm by estimation the thickness of fog in the input image as well as the output image. Finally, the simulation results and visualisation of defogged images indicate that the proposed defogged algorithm is highly effective and efficient for visibility enhancement of foggy images. 2018 Karabuk University | en_US |
dc.title | A robust framework for visibility enhancement of foggy images | en_US |
dc.type | Article | en_US |
Appears in Collections: | 1. Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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21 A robust framework.pdf | 4.16 MB | Adobe PDF | View/Open |
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