An improved algorithm of multi-exposure image fusion by detail enhancement

Abstract

Multi-exposure image fusion is an effective method for depicting high dynamic range of the target scene in a single image. However, there are still some problems remaining: the preserving of global contrast, the preserving of the local details in saturated regions, and the existence of halo artifacts. To solve these problems, this paper proposes a new multi-exposure image fusion algorithm with detail enhancement. Firstly, the well-exposedness evaluation function, the chromatic information evaluation function and the local detail preserved function are used to measure weight maps. Then, an improved multi-exposure fusion framework based on pyramid decomposition is proposed to further enhance the details. The experimental results demonstrate that the proposed algorithm can preserve more details than the state-of-the-art. In the view of appreciation, our approach could produce a more realistic brightness distribution of target scene as well as avoid halo artifacts.