Paper Info
Title
Light Field Compression of HDCA Images Combining Linear Prediction and JPEG 2000.
Abstract
We have proposed under JPEG Pleno standardization activities a scheme for lenslet image compression, where the regularities and similarities existing between neighbor angular views were successfully exploited, achieving competitive results in the JPEG Pleno core experiments using lenslet data. This paper proposes improvements on our previous scheme of light field compression, making our approach more suitable for compression of light fields acquired with dense camera arrays, where the disparities between farthest views can reach several hundreds of pixels. We review the functional blocks of the compression algorithm, replacing and modifying some of the functionality with more advanced and efficient solutions. Based on our submission to the JPEG Pleno core experiments, we present and discuss our results obtained on the Fraunhofer HDCA dataset. Additionally, we present a new view merging algorithm which substantially increases the PSNR at all bit rates.
Year
DOI
Venue
2018
10.23919/EUSIPCO.2018.8553482
European Signal Processing Conference
Field
DocType
ISSN
Lenslet,Computer vision,Computer science,Transform coding,Linear prediction,JPEG,Pixel,Artificial intelligence,JPEG 2000,Data compression,Image compression
Conference
2076-1465
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Pekka Astola1204.98
Ioan Tabus227638.23