Applied Sciences (Jun 2022)

Multi-Exposure Image Fusion Based on Weighted Average Adaptive Factor and Local Detail Enhancement

  • Dou Wang,
  • Chao Xu,
  • Bo Feng,
  • Yunxue Hu,
  • Wei Tan,
  • Ziheng An,
  • Jubao Han,
  • Kai Qian,
  • Qianqian Fang

DOI
https://doi.org/10.3390/app12125868
Journal volume & issue
Vol. 12, no. 12
p. 5868

Abstract

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In order to adapt to the local brightness and contrast of input image sequences, we propose a new weighted average adaptive factor well-exposure weight evaluation scheme. The exposure weights of brighter and darker pixels are determined according to the local average brightness and expected brightness. We find that in the traditional multi-exposure image fusion scheme, the brighter and darker regions of the scene lose many details. To solve this problem, we first propose a standard to determine the brighter and darker regions and then use a fast local Laplacian filter to enhance the image in the region. This paper selects 16 multi-exposure images of different scenes for subjective and objective analysis and compares them with eight existing multi-exposure fusion schemes. The experimental results show that the proposed method can enhance the details appropriately while preserving the details in static scenes and adapting to the input image brightness.

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