Paper Info
Title
Symmetrical predictor structure based integrated lossy, near lossless/lossless coding of images
Abstract
Prediction based algorithms reported in the literature are not able to integrate lossy and near-lossless/lossless coding and uses only causal pixels (non-symmetrical predictor structure) for prediction. A non-symmetrical predictor structure, however, is not able to efficiently adapt near the intensity varying areas, which results into poor prediction. Hence, we propose a novel two-stage algorithm for lossy, near lossless/lossless compression using a symmetrical predictor structure is proposed. In the first stage, the proposed algorithm encodes and decodes the given image using the JPEG-2000 standard algorithm (lossy coding). This JPEG-2000 decoded image in the first stage, enables us to use the symmetrical predictor (using both causal and non-causal pixels) for prediction in the second stage. A performance evaluation shows that our algorithm is significantly better in terms of compression performance as compared to some of the computationally complex methods.
Year
DOI
Venue
2014
10.1109/ISCAS.2014.6865629
Circuits and Systems
Keywords
Field
DocType
data compression,image coding,prediction theory,JPEG-2000 decoded image,JPEG-2000 standard algorithm,causal pixel,compression performance,image decoding,image encoding,integrated lossy image coding,near lossless-lossless image coding,nonsymmetrical predictor structure,prediction based algorithm,Computational Complexity,Near-lossless and Lossless Image Compression,Symmetrical Predictor Structure
JBIG2,Lossless JPEG,Entropy encoding,Pattern recognition,Lossy compression,Computer science,Artificial intelligence,Data compression,Image compression,Lossless compression,Context-adaptive binary arithmetic coding
Conference
ISSN
Citations 
PageRank 
0271-4302
2
0.37
References 
Authors
8
5
Name
Order
Citations
PageRank
Vinit Jakhetiya110212.89
Oscar C. Au21592176.54
Sunil Prasad Jaiswal3427.94
Luheng Jia4225.35
Gaurav Mittal516021.03