Open AccessImage fusion‐based video deraining using sparse representation
Author(s) -
Mi Zetian,
Shang Jinxia,
Zhou Huan,
Wang Minghui
Publication year - 2016
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.2016.1451
Subject(s) - artificial intelligence , computer science , representation (politics) , computer vision , image fusion , sparse approximation , fusion , image (mathematics) , pattern recognition (psychology) , linguistics , philosophy , politics , political science , law
By disregarding the ‘rain component’ but keeping the ‘non‐rain component’ only, results reconstructed by the conventional morphological component analysis decomposition‐based rain removal algorithms lose a lot of detail information. On the basis of the limitation, an image fusion strategy is introduced to remove rain from a video. The final rain‐free frame is recovered by employing the fused coefficients and the fused dictionary. Experimental results demonstrate that the proposed method can efficiently remove rain streaks, while at the same time preserve more detail information.