Transfer of content-aware vignetting effect from paintings to photographs

Abstract

This paper discusses how the vignetting effect of paintings may be transferred to photographs, with attention to center-corner contrast. First, the lightness distribution of both are analyzed. The results show that the painter’s vignette is more complex than that achieved using common digital post-processing methods. It is shown to involve both the 2D and 3D geometry of the scene. Then, an algorithm is developed to transfer the vignetting effect from an example painting to a photograph. The example painting is selected as that has similar contextual geometry with the photograph. The lightness weighting pattern extracted from the selected example painting is adaptively blended with the input photograph to create vignetting effect. In order to avoid over-brightened or over-darkened regions in the enhancement result, the extracted lightness weighting pattern is corrected using a nonlinear curve. A content-aware interpolation method is also proposed to warp the lightness weighting to fit the contextual structure of the photograph. Finally, the local contrast is restored. Experiments show that the proposed algorithm can successfully perform this function. The resulting vignetting effect is more naturally presented with regard to esthetic composition as compared with vignetting achieved with popular software tools and camera models.