• Dharmendra Verma
• Pankaj Shrivastava

This paper provides a description of different methods for the elimination of haze. Fog brings issues for most graphics PC vision uses while it decreases the exposure of a scene. Fog is created by two fundamental phenomena. that could be attenuation and light of air. Attenuation decreases contrast & light of air increases the whiteness of the scene. Fog removal (FR) systems recover the color & contrast of the scene. Reported algorithms for FR were reviewed in this journal. Fog reduces (FRD) the illumination of the scene so the performance of more than different computer vision algorithms use features information. It's the fog formation Perform depth of fog. Analysis of depth data is a constraint barrier if a single image is available. Consequently, the removal of fog require assumptions or prior data. FR algorithms estimate the depth of the data quite a lot of assumptions, that are mentioned in important points right here. FR algorithm has a broad application in navigation & monitoring, entertainment industries & electronics

Radiation; Advection; Upslope; Freezing; Evaporation or Mixing; Dark Channel Prior; CLAHE; Bilateral Filtering; MIX – CLAHE and Trilateral Filtering, etc

"A Review: Fog Removal Techniques with its Types and Limitation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.308-313, June 2019, Available :http://www.jetir.org/papers/JETIR1908510.pdf

"A Review: Fog Removal Techniques with its Types and Limitation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp308-313, June 2019, Available at : http://www.jetir.org/papers/JETIR1908510.pdf