We propose an objective quality assessment method for image retargeting. The key step in our approach is to generate a structural similarity (SSIM) map that indicates at each spatial location in the source image how the structural information is preserved in the retargeted image. A spatial pooling method employing both bottom-up and top-down visual saliency estimations is then applied to provide an overall evaluation of the retargeted image. To evaluate the performance of the proposed IR-SSIM algorithm, we created an image database that contains images produced by different retargeting algorithms and carried out subjective tests to assess the quality of the retargeted images. Our experimental results show that IR-SSIM is better correlated with subjective evaluations than existing methods in the literature. To further demonstrate the advantages and potential applications of IR-SSIM, we embed it into a multi-operator image retargeting process, which generates visually appealing retargeting results.