Open AccessExemplar-based image completion using image depth information
Author(s) -
Mang Xiao,
Guangyao Li,
Li Xie,
Lei Peng,
Qiaochuan Chen
Publication year - 2018
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0200404
Subject(s) - artificial intelligence , image (mathematics) , computer science , computer vision , feature detection (computer vision) , image gradient , image texture , automatic image annotation , consistency (knowledge bases) , image restoration , image processing , pattern recognition (psychology)
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.