Detail-Preserving Multi-Exposure Fusion with Edge-Preserving Structural Patch Decomposition

Hui Li, Tsz Nam CHAN, Xianbiao Qi, Wuyuan Xie

Research output: Contribution to journalArticlepeer-review

Abstract

The multi-exposure fusion (MEF) methods have received much attention in recent years due to the importance of constructing high dynamic range images. Among most of the existing studies, multi-scale structural-patch-decomposition-based MEF (MSPD-MEF) has achieved state-of-the-art fusion quality and the fastest running time. However, this method still suffers from detail loss in the fused images. To tackle this issue, we first incorporate the edge-preserving factors into this method to preserve the details in the fused images in a single-scale setting. Then, we develop the novel and flexible bell curve function, which can further preserve the details in both bright and dark regions. After that, we also show that our method can seamlessly plug in to this multi-scale framework. Extensive experimental results indicate that the proposed method can produce pleasing fusion results with little artifacts and low computational cost in both static and dynamic scenes.

Original languageEnglish
JournalIEEE Transactions on Circuits and Systems for Video Technology
DOIs
Publication statusAccepted/In press - 2021

Scopus Subject Areas

  • Media Technology
  • Electrical and Electronic Engineering

User-Defined Keywords

  • Computational efficiency
  • Dynamic range
  • edge-preserving
  • high dynamic range imaging
  • Image edge detection
  • Kernel
  • Multi-exposure fusion
  • Smoothing methods
  • structural patch decomposition
  • Task analysis
  • Visualization

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