Exploiting patch-based correlation for ghost removal in exposure fusion

Abstract

In this paper, we present a robust exposure fusion algorithm to tackle the problems of motion removal and detail preserving in dynamic scenes. With one exposure as reference, the motion appeared in the exposure stack can be detected by comparing the structural consistency, which is extracted by measuring the degree of linear correlation between the patches of the reference image and the other source images. Then, a stack of latent images with consistent contents can be synthesized after motion removal. For detail preserving, a contrast criterion is introduced to measure the exposedness and generate visibility maps of each latent image. Guided by the visibility maps, a tonemapped-like HDR image which is ghost-free and with all details preserved could be produced by seamlessly merging the latent images. Exposure fusion tests on various dynamic scenes demonstrate the superiority of the proposed method over existing state-of-the-art approaches.