Paper Info
Title
Depth image interpolation using confidence-based markov random field
Abstract
Depth images are essential data for high-quality three-dimensional (3D) video services, but the resolution of depth images captured by commercially available depth cameras is lower than that of the corresponding color images, owing to technical limitations. A depth image up-sampling method that uses a confidence-based Markov random field is proposed for enhancing this resolution. An initial high-resolution depth image and confidence values are generated with consideration of boundaries and textures in the corresponding color images. These are used as the base for a new likelihood and prior model design. The energy function derived from this model is optimized by using a graph cut algorithm, and subsequent experiments show that the proposed algorithm provides sufficiently good up-sampled depth images compared to other state-of-the-art algorithms.
Year
DOI
Venue
2012
10.1109/TCE.2012.6415012
IEEE Trans. Consumer Electronics
Keywords
Field
DocType
energy function,video signal processing,depth image up-sampling method,prior model design,graph cut algorithm,depth camera,interpolation,confidence-based markov random field,image resolution,depth image resolution,depth image interpolation,color images,high-quality 3d video services,high-quality three-dimensional video services,markov random field (mrf),image sampling,cameras,depth cameras,resolution enhancement,confidence,graph theory,textures,confidence value,image texture,image enhancement,depth image,markov processes,image colour analysis,likelihood model design,color,algorithm design and analysis
Computer vision,Pattern recognition,Markov random field,Computer science,Binary image,Image processing,Demosaicing,Image formation,Artificial intelligence,Digital image processing,Image resolution,Color image
Journal
Volume
Issue
ISSN
58
4
0098-3063
Citations 
PageRank 
References 
4
0.44
11
Authors
2
Name
Order
Citations
PageRank
Jaeil Jung117426.82
Yo-Sung Ho21288146.57