Multiexposure image fusion (MEF) is an effective approach to generate high dynamic range images from multilevel exposures taken from ordinary cameras. In this article, a novel MEF algorithm is proposed to gain maximum visual details as well as vivid colors from the captured scene. This algorithm first decomposes the input images with multiple exposures into the base and detail layer. The weights for the base and detail layers are computed by using exposedness function and then both the layers are combined to generate the final fused image. The proposed multiexposure technique requires fewer computational operations, preserves edges, and also reduces spatial artifacts. The proposed technique has been evaluated quantitatively using image quality assessment model based on structure similarity index measure for MEF. By the extensive experimental results, it has been illustrated that in addition to significantly outperforming other state-of-the-art techniques, the proposed technique is much faster and can achieve better image quality.
Keywords: bilateral filter; exposedness function; image enhancement; multiexposure image fusion; quality measure.