Defogging of Visual Images Using SAMEER-TU Database | Zendy

Tannistha Pal | Zendy; Mrinal Kanti Bhowmik | Zendy; Anjan Ghosh | Zendy

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Defogging of Visual Images Using SAMEER-TU Database

Author(s) -

Tannistha Pal,

Mrinal Kanti Bhowmik,

Anjan Ghosh

Publication year - 2015

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2015.02.108

Subject(s) - computer science , visibility , robustness (evolution) , computer vision , fidelity , ground truth , artificial intelligence , contrast (vision) , optics , telecommunications , biochemistry , chemistry , physics , gene

Poor visibility in foggy condition is a serious problem for computer vision applications. Most computer vision applications suppose that the input images should have clear visibility but due to foggy conditions, images lose the contrast and color-fidelity, and, therefore, improving visibility is an inevitable task. This paper presents a newly created SAMEER–TU database consisting of 5390 images captured in foggy as-well-as, in clear condition with useful ground truth information. This paper also describes a method towards enhancing the visibility of the foggy images. Finally for verifying robustness of the method, qualitative assessment evaluation is performed as a contributory step

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