Paper Info
Title
Image set modeling by exploiting temporal-spatial correlations and photo album compression
Abstract
With the advance of digital photographing technology, large amount of personal photos are created and stored online or in personal computers. To save storage space and transmission bandwidth, we proposed a new photo album compression scheme by using both intra prediction and inter prediction to reduce spatial and temporal redundancy. Specifically, we first cluster the images so that each cluster containing a set of similar images is a group of pictures (GOP) with variable length. A graph framework is proposed then, in which an optimal “IPPP...P” GOP structure is derived from every cluster by finding the minimum spanning tree (MST) at a minimum prediction cost. Finally, the photo album is compressed as a whole like a video sequence, by High Efficiency Video Coding (HEVC), according to the predictive order of the optimal structures. The experimental results show that our scheme achieves around 60% improvement over only using JPEG compression.
Year
Venue
Keywords
2012
APSIPA
storage space,intraprediction,image coding,digital photographing technology,photo album compression,trees (mathematics),graph framework,data compression,personal computer,transmission bandwidth,temporal-spatial correlation,image set modeling,minimum spanning tree,prediction theory,spatial redundancy reduction,group of pictures,prediction cost,jpeg compression,personal photo,interprediction,temporal redundancy reduction
Field
DocType
ISSN
Compression (physics),Computer vision,Graph,Group of pictures,Coding (social sciences),Redundancy (engineering),Transmission bandwidth,Artificial intelligence,Data compression,Mathematics,Minimum spanning tree
Conference
2309-9402
ISBN
Citations 
PageRank 
978-1-4673-4863-8
2
0.38
References 
Authors
4
5
Name
Order
Citations
PageRank
Ruobing Zou1666.05
Oscar C. Au21592176.54
Guyue Zhou331.42
Sijin Li4153.20
Lin Sun51557.90