@Article{rig.2019.00091,
AUTHOR = {Safa Ridene
, Reda Yaagoubi, Imane Sebari,
Audrey Alajouanine},
TITLE = {Shadow detection and correction using a combined 3D GIS and image processing approach},
JOURNAL = {Revue Internationale de Géomatique},
VOLUME = {29},
YEAR = {2019},
NUMBER = {3},
PAGES = {241--253},
URL = {http://www.techscience.com/RIG/v29n3/52831},
ISSN = {2116-7060},
ABSTRACT = {While shadow can give useful information about size and shape of objects, it can pose
problems in feature detection and object detection, thereby, it represents one of the major
perturbator phenomenons frequently occurring on images and unfortunately, it is inevitable.
“Shadows may lead to the failure of image analysis processes and also cause a poor quality of
information which in turn leads to problems in implementation of algorithms.” (Mahajan and
Bajpayee, 2015). It also affects multiple image analysis applications, whereby shadow cast by
buildings deteriorate the spectral values of the surfaces. Therefore, its presence causes a
deterioration in the visual image’s quality and limits the information that the former could give.
Ignoring the existence of shadows in images may cause serious problems in various visual
processing applications such as false objects detection. In this context, many researches have
been conducted through years. However, it is still a challenge for analysts all over the world to
find a fully automated and efficient method for shadow removal from images.},
DOI = {10.3166/rig.2019.00091}
}