Open AccessEdge‐based spatial concealment of digital dropout error in degraded archived media
Author(s) -
Hoque Md. Monirul,
Leonel Quiroa Pimentel Mario,
Hasan Md. Mehedi,
Ahn Kiok,
Kim Jaemyun,
Chae Oksam
Publication year - 2014
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2014.1055
Subject(s) - dropout (neural networks) , enhanced data rates for gsm evolution , computer science , artificial intelligence , computer vision , remote sensing , computer graphics (images) , geography , machine learning
A spatial concealment technique, based on the concept of the strength of an edge, is proposed for ‘digital dropout’ error, evident in old archived media. As long as the presence of pathological motion is observed in video sequences where current state‐of‐the‐art methods fail to reproduce correct information, such spatial restoration offers a much better solution in terms of quality and complexity. Furthermore, relevant edge‐based weighted interpolation is able to restore complicated edges and complex textures from the available neighbourhood. An experiment is performed on real video archives to evaluate the efficacy of the proposed technique.