Open AccessLayered‐based exposure fusion algorithm
Author(s) -
Li Xiaoguang,
Li Fenghui,
Zhuo Li,
Feng David Dagan
Publication year - 2013
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2012.0494
Subject(s) - luminance , robustness (evolution) , computer science , computer vision , artificial intelligence , fusion , image fusion , algorithm , image (mathematics) , biochemistry , chemistry , linguistics , philosophy , gene
Owing to the limitation of dynamic range, a single still image is usually insufficient to describe a high contrast scene. Fusing multi‐exposure images of the same scene can produce a resulting image with details both in the bright and the dark regions. However, they may be sensitive to the exposure parameters of the input images. In this study, a global layer is introduced to improve the robustness of the fusion method. The global layer is employed to preserve the overall luminance of a real scene and avoid possible luminance reversion artefacts. Then, details are recovered in the gradient domain by a Poisson solver. Experimental results show the superior performance of our approach in terms of robustness and details preservation.