Paper Info
Title
A Unified Framework for Lossless Image Set Compression
Abstract
As the availability and use of digital images increase, the efficient storage of images becomes an important area of research. Traditionally, each image in a set is compressed individually, taking advantage of the redundancies existing within the image. In the related area of video compression, a video sequence is decomposed into individual frames. Video compression algorithms take advantage of redundancy existing among consecutive frames as well as the redundancy existing within each frame. Unlike video compression, there are applications that use large image sets whose inter-image relationships are unknown. For example, a medical database may contain a large number of X-ray images of the same body part; a database of satellite images may possess "similar" characteristics; a database of facial images contains many similar images. In some applications compressed images must be identical to the original images, therefore lossless compression must be used.
Year
DOI
Venue
2006
10.1109/DCC.2006.4
DCC
Keywords
DocType
ISSN
set compression,video compression,medical database,lossless compression,facial image,unified framework,x-ray image,large image set,lossless image,original image,video compression algorithm,digital images increase,video sequence,tree graphs,computer science,data compression,minimum spanning tree,image compression,digital images,first order,spanning tree,mathematics,biomedical imaging
Conference
1068-0314
ISBN
Citations 
PageRank 
0-7695-2545-8
7
0.68
References 
Authors
5
3
Name
Order
Citations
PageRank
Barry Gergel1252.84
Howard Cheng213718.85
Xiaobo Li36410.79