Open AccessRemoving Rain Component from A Color Image
Publication year - 2021
Publication title -
international journal of emerging trends in engineering research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 14
ISSN - 2347-3983
DOI - 10.30534/ijeter/2021/12942021
Subject(s) - rain and snow mixed , visibility , computer vision , computer science , artificial intelligence , haze , component (thermodynamics) , snow , image quality , image processing , task (project management) , snow removal , image (mathematics) , computer graphics (images) , geography , engineering , meteorology , physics , systems engineering , thermodynamics
It is well-known that a bad weather, e.g. haze, rain, or snow affects severely the quality of the captured images or videos. Also raindrops adhered to a glass window or camera lens can severely affect the visibility of background scene and degrade the image quality, which consequently degrades the performance of many image processing and computer vision system algorithms. These algorithms are used in various applications such as object detection, tracking, recognition, and surveillance also in navigation. Rain removal from a video or a single image has been an active research topic over the past decade. Today, it continues to draw attentions in outdoor vision systems (e.g. surveillance) where the ultimate goal is to produce a clear and clean image or video. The most critical task here is to separate rain component from the other part. For that purpose, we are proposing an efficient algorithm to remove rain from a color image.