Exemplar-based image completion using image depth information

Image completion techniques are required to complete missing regions in digital images. A key challenge for image completion is keeping consistency of image structures without ambiguity and visual artifacts. We propose a novel method for image completion using image depth cue. Our method includes three major features. First, we compute the image gradient to improve image completion when searching for the most similar patches. Second, using image depth, we guide image completion by means of appropriate scale transformation. Third, we propose a global optimization patch-based method having gradient and depth features for image completion. Experiments demonstrate that our approach is a potentially superior method for completing missing regions.