Algorithm of multiexposure image fusion with detail enhancement and ghosting removal

Abstract

Multiexposure image fusion is an effective method for depicting a high dynamic range display of target scenes. However, the loss of local details and ghosting artifacts in fusion images has not yet been well resolved in the existing research. To solve these problems, a multiexposure image fusion algorithm with detail enhancement and ghosting removal is proposed. First, the exposure brightness and chromaticity information in YIQ color space are used to measure weight maps. When the captured scene is dynamic with moving objects, the weight maps are refined to remove ghosting artifacts based on the image difference and superpixel segmentation. Finally, an improved Laplacian pyramid fusion framework is proposed to achieve image fusion with detail enhancement. The experimental results demonstrate the effectiveness of the proposed method in terms of both visual quality and objective evaluation and show that the proposed algorithm can preserve more details and can remove ghosting artifacts effectively.