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Real-time precipitation suppression in video streams

Nilsson, Adam LU and Truong, Hoa LU (2014) EDA920 20141
Department of Computer Science
Abstract
In surveillance cameras rain and snow can introduce an unwelcome noise to the video stream. The resulting effect of the rain becomes bright streaks in the frames of the video. These streaks can disturb human viewers and image processing algorithms.

Rain streaks can be hard to detect and remove as they are a very dynamic phenomenon dependent on camera settings and weather conditions. This thesis aims to research some already invented rain removal algorithms and compare and evaluate them. Surveillance cameras supply video in real-time so it is not possible to access the whole video and perform heavy computations relying on information from the future.

Qualities such as level of streak suppression and time required to perform necessary... (More)
In surveillance cameras rain and snow can introduce an unwelcome noise to the video stream. The resulting effect of the rain becomes bright streaks in the frames of the video. These streaks can disturb human viewers and image processing algorithms.

Rain streaks can be hard to detect and remove as they are a very dynamic phenomenon dependent on camera settings and weather conditions. This thesis aims to research some already invented rain removal algorithms and compare and evaluate them. Surveillance cameras supply video in real-time so it is not possible to access the whole video and perform heavy computations relying on information from the future.

Qualities such as level of streak suppression and time required to perform necessary calculations are weighed against each other. (Less)
Please use this url to cite or link to this publication:
author
Nilsson, Adam LU and Truong, Hoa LU
supervisor
organization
course
EDA920 20141
year
type
H2 - Master's Degree (Two Years)
subject
keywords
rain-detection, image enhancement, rain-removal
language
English
id
4499675
date added to LUP
2014-08-15 12:51:02
date last changed
2014-09-04 08:29:49
@misc{4499675,
  abstract     = {{In surveillance cameras rain and snow can introduce an unwelcome noise to the video stream. The resulting effect of the rain becomes bright streaks in the frames of the video. These streaks can disturb human viewers and image processing algorithms. 

Rain streaks can be hard to detect and remove as they are a very dynamic phenomenon dependent on camera settings and weather conditions. This thesis aims to research some already invented rain removal algorithms and compare and evaluate them. Surveillance cameras supply video in real-time so it is not possible to access the whole video and perform heavy computations relying on information from the future.

Qualities such as level of streak suppression and time required to perform necessary calculations are weighed against each other.}},
  author       = {{Nilsson, Adam and Truong, Hoa}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Real-time precipitation suppression in video streams}},
  year         = {{2014}},
}