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

Abstract

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.