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.