A perceptual image completion approach based on a hierarchical optimization scheme

This paper aims to introduce a novel efficient approach for high-quality and fast image restoration by combining 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 the superiority of the proposed method in terms of image quality and computational time.