A perceptual image completion approach based on a hierarchical optimization scheme

•A novel inpainting method based on multi-resolution representation is proposed.•A framework using combination of greedy and global optimization strategies.•Improvement of greedy strategies priority to restore the lowest resolution image.•Offset maps used to interpolate from lower resolution and refined using graph cuts.•Obtained results outperform objectively and subjectively state-of-the-art methods.

This paper aims at introducing a novel efficient approach for high-quality and fast image restoration by combining both a greedy strategy and a global optimization strategy, based on a pyramidal representation of the image. A coarse version of the input image is first restored by exemplar-based method using a greedy strategy. From the low-resolution inpainted image, higher resolutions are interpolated and refined by a global optimization strategy. Experimental results on natural images demonstrate the effectiveness of the proposed method. Moreover, a comparison with some methods of the state-of-the-art confirms its superiority in terms of image quality and computational time.