Paper Info
Title
Weighted Ratio-Based Adaptive Lossless image coding
Abstract
In this paper, we present an image compression algorithm called Weighted, Ratio-Based, Adaptive, Lossless image Codec (WRALIC). The algorithm utilizes 5 ratio predictions. The weight of each prediction is learned during a training stage offline, whereas the prediction parameters are adjusted using error context. The absolute value of the error is encoded. The algorithm does not encode the sign. Instead, it attempts to guess the sign of the error from the sign context of the pixel. Using the energy and the average errors around a pixel, the error is added to an encoding bin. Experimental results demonstrate good compression performance compared to other state of the art algorithms.
Year
DOI
Venue
2014
10.1109/CCECE.2014.6901106
Electrical and Computer Engineering
Keywords
Field
DocType
adaptive codes,data compression,image coding,WRALIC algorithm,context modeling,image compression,lossless compression,weighted ratio-based adaptive lossless image coding,adaotive prediction,context modeling,entropy coding,image compression,lossless compression
Data compression ratio,Entropy encoding,Pattern recognition,Lossy compression,Computer science,Prediction by partial matching,Artificial intelligence,Data compression,Image compression,Lossless compression,Adaptive coding
Conference
ISSN
Citations 
PageRank 
0840-7789
0
0.34
References 
Authors
5
2
Name
Order
Citations
PageRank
AbdulWahab Kabani121.38
Mahmoud R. El-Sakka2102.25