Jia, W., Song, Z., & Li, Z. (2022). Multi-Scale Exposure Fusion via Content Adaptive Edge-Preserving Smoothing Pyramids. IEEE Transactions on Consumer Electronics, 68(4), 317–326. https://doi.org/10.1109/tce.2022.3200707
Abstract:
Multi-scale exposure fusion (MEF) is an efficient
way to fuse differently exposed low dynamic range (LDR) images
of a high dynamic range (HDR) scene into an information
enriched LDR image. In this paper, a new MEF algorithm is
proposed to merge the differently exposed LDR images by introducing
novel content adaptive edge-preserving smoothing (CAS)
pyramids for the weight maps of all the LDR images. With the
proposed CAS pyramids, details in the brightest and darkest
regions of the HDR scene are preserved better than existing MEF
algorithms on top of the Gaussian pyramids and edge-preserving
smoothing pyramids. Comparisons experimentally demonstrate
the effectiveness of the proposed algorithm to nine state-of-theart
MEF algorithms from both subjective and objective points
of view regardless the image sizes
License type:
Publisher Copyright
Funding Info:
There was no specific funding for the research done