Title
Scalable coding of plenoptic images by using a sparse set and disparities.
Abstract
One of the light field capturing techniques is the focused plenoptic capturing. By placing a microlens array in front of the photosensor, the focused plenoptic cameras capture both spatial and angular information of a scene in each microlens image and across microlens images. The capturing results in significant amount of redundant information, and the captured image is usually of a large resolution. A coding scheme that removes the redundancy before coding can be of advantage for efficient compression, transmission and rendering. In this paper, we propose a lossy coding scheme to efficiently represent plenoptic images. The format contains a sparse image set and its associated disparities. The reconstruction is performed by disparity-based interpolation and inpainting, and the reconstructed image is later employed as a prediction reference for the coding of the full plenoptic image. As an outcome of the representation, the proposed scheme inherits a scalable structure with three layers. The results show that plenoptic images are compressed efficiently with over 60 percent bit rate reduction compared to HEVC intra, and with over 20 percent compared to HEVC block copying mode.
Year
DOI
Venue
2016
10.1109/TIP.2015.2498406
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Keywords
Field
DocType
image coding,image reconstruction,interpolation,disparity-based interpolation,image inpainting,image reconstruction,lossy coding scheme,microlens image,photosensor,plenoptic images,scalable coding scheme,sparse image set,HEVC,Plenoptic,compression,light field
Iterative reconstruction,Computer vision,Pattern recognition,Computer science,Bit Rate Reduction,Image processing,Light field,Inpainting,Sparse image,Artificial intelligence,Image-based modeling and rendering,Rendering (computer graphics)
Journal
Volume
Issue
ISSN
25
1
1941-0042
Citations 
PageRank 
References 
21
1.02
24
Authors
4
Name
Order
Citations
PageRank
Yun Li1583.72
Mårten Sjöström217419.69
Roger Olsson3575.64
Ulf Jennehag421717.01