Recently, digital image inpainting has attracted strong research interest because of its extensive applications in real life. The terminology “inpainting” refers to automatic restoration of image defects such as scratches or blotches as well as removal of unwanted objects as, for instance, subtitles, logos, etc, such that it is undetectable by viewers without the reference to the original image. Many works on this subject have been published in recent years. This paper introduces a novel unsupervised image completion framework using a modified exemplar-based method in conjunction with a pyramidal representation of an image. A top-down iterative completion is performed gradually with multi-resolution patches and a window-based priority. The proposed approach is verified on different natural images. Also, a comparison with some existing methods coming from literature is carried out and the results show improvement in favor of our approach.