Paper Info
Title
Lossless image compression with lossy image using adaptive prediction and arithmetic coding
Abstract
Lossless gray scale image compression is necessary for many purposes, such as medical imaging, image databases and so on. Lossy images are important as well, because of the high compression ratio. The authors propose a lossless image compression scheme using a lossy image generated with the JPEG-DCT scheme. The concept is, send a JPEG-compressed lossy image primarily, then send residual information and reconstruct the original image using both the lossy image and residual information. 3D adaptive prediction and adaptive arithmetic coding are used, which fully use the statistical parameters of the distribution of the symbol source. The optimal number of neighbor pixels and lossy pixels used for prediction is discussed. The compression ratio is better than previous work and quite close to the original lossless algorithm
Year
DOI
Venue
1994
10.1109/DCC.1994.305924
Data Compression Conference
Keywords
Field
DocType
data compression,discrete cosine transforms,filtering and prediction theory,image coding,image reconstruction,3D adaptive prediction,JPEG-DCT scheme,adaptive arithmetic coding,compression ratio,lossless gray scale image compression,lossy images,neighbor pixels numbers,reconstruction,residual information,statistical parameter,symbol source
JBIG2,Computer vision,Data compression ratio,Lossy compression,Computer science,Color Cell Compression,Theoretical computer science,JPEG,Artificial intelligence,Data compression,Image compression,Lossless compression
Conference
Citations 
PageRank 
References 
12
5.44
0
Authors
2
Name
Order
Citations
PageRank
Seishi TAKAMURA17526.11
Mikio Takagi2221198.87