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    Abstract
2017 (Vol. 14, Issue: 9)
Research Article

Reflection Removal Algorithms: A Review

Yossra H. Ali and Maisa S. Mohsen
Computer Sciences Department, University of Technology, Sinaa'a Street, Baghdad, Iraq
 

DOI: 10.19026/rjaset.14.5075
Submitted Accepted Published
June 24, 2017 ‎July 22, 2017 September 15, 2017

  How to Cite this Article:

Yossra H. Ali and Maisa S. Mohsen, 2017. Reflection Removal Algorithms: A Review.  Research Journal of Applied Sciences, Engineering and Technology, 14(9): 347-351.

DOI: 10.19026/rjaset.14.5075

URL: http://www.maxwellsci.com/jp/mspabstract.php?jid=RJASET&doi=rjaset.14.5075

Abstract:


This study describes some algorithms in literature review that tried to computationally remove reflections from images over the past years and explains the advantages, limitations or drawbacks of these algorithms. With the popularity of all kinds of digital instrument and digital products, image has become one of the most commonly information carriers in the human activity. The image quality is often influenced by a variety of external factors. When you're going to travel, in some cases, you may have to take pictures through the dividing glass because you are unable to get off the vehicle. You may want to take photographs through windows when you are in a coffee shop or high rise building, this resulted to undesired reflections in the photograph and loss of information in the scene we actually want to capture and destroy the picture, so reflection in images is a big problem in photography. In computer vision, removing reflections is a very useful pre-processing step to remove undesired information from the image to be analyzed, to reach this goal many algorithms have been developed.

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    Competing interests

The authors have no competing interests.
    Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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© The Author(s) 2017

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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