Improving Photo Composition Elegantly: Considering Image Similarity During Composition

Abstract

Optimization of images with bad compositions has attracted increasing attention in recent years. Previous methods however seldomly consider image similarity when improving composition aesthetics. This may lead to significant content changes or bring large distortions, resulting in an unpleasant user experience. In this paper, we present a new algorithm for improving image composition aesthetics, while retaining faithful, as much as possible, to the original image content. Our method computes an improved image using a unified model of composition aesthetics and image similarity. The term of composition aesthetics obeys the rule of thirds and aims to enhance image composition. The similarity term in contrast penalizes image difference and distortion caused by composition adjustment. We use an edge-based measure of structure similarity which nearly coincides with human visual perception to compare the optimized image with the original one. We describe an effective scheme to generate the optimized image with the objective model. Our algorithm is able to produce the recomposed images with minimal visual distortions in an elegant and user controllable manner. We show the superiority of our algorithm by comparing our results with those by previous methods.