Open AccessFoggy Image Detection and Filtration Methods: Review
Author(s) -
. Priyanka,
Geetanjali Babbar
Publication year - 2021
Publication title -
cgc international journal of contemporary technology
Language(s) - English
Resource type - Journals
ISSN - 2582-0486
DOI - 10.46860/cgcijctr.2021.06.31.211
Subject(s) - fogging , computer vision , artificial intelligence , haze , computer science , brightness , filter (signal processing) , smoothing , image restoration , image (mathematics) , image quality , image fusion , remote sensing , environmental science , image processing , geography , optics , physics , meteorology
Image de-fogging in brightness defined to image calculated in a deprived climate like as fog, rain and ocean and pollutants or dust particles. To alter the fog and some other pollutants from the image, various methods are customized, some mainly utilized methods are DCP, Detection, and Classification of foggy images. Haze is an arrangement of dual components, air-light and DA (Direct Attenuation), low image quality and generates various issues in VS (Video Surveillance), Navigation and Target Tracking, etc. So, its removes from an image, several de-fogging approaches have been discussed in this paper. Image De-fogging can attain utilizing several and single image haze removal techniques. The famous methods are discussed in this paper used for image de-fogging in DCP, Depth-map for accurate estimation, Guided Filter, and Transmission methods. These techniques still efficient in removing haze from images have very high time complexity. The guided filter is a new region preservative filter with region enhancement and smoothing. The previous result was a local linear transformation of the Guided Image. It defines a review of the classification and detection technique of a hazy image. This method mitigates the limitations of filtration and DCP and at the same time preserves the image quality. At that time, described the existing image de-fogging methods containing image restoration, contrast improvement, and fusion-based image de-fogging methods.