DocumentCode
3384544
Title
Differentiation-based multi-resolution approach for lossless image compression
Author
Qi, Xiaojun ; Tyler, John M.
Author_Institution
Dept. of Comput. Sci., Utah State Univ., Logan, UT, USA
fYear
2003
fDate
25-27 March 2003
Firstpage
445
Abstract
Summary form only given. A differentiation-based multi-resolution approach for lossless image compression was presented. The technique used six appropriately weighted adjacent pixels to estimate the predicted pixel intensity. It can also be considered as an additional rule for the seven predictors used by lossless JPEG. The prediction error was decomposed by integer wavelet transform to improve the prediction. The minimum weighted entropy determines the optimal decomposition level of the differentiation-based wavelet transform. The performance of the proposed approach was evaluated and compared with the lossless JPEG and lossless adaptive linear predictor schemes. These two techniques are capable of estimating the present pixel value from the previous pixel values. The computational complexities were greatly reduced due to known values of the predictor coefficients used by the encoder and decoder.
Keywords
data compression; differentiation; image coding; image resolution; minimum entropy methods; prediction theory; wavelet transforms; adjacent pixels; computational complexities; decoder coefficients; differentiation-based multiresolution approach; encoder coefficients; integer wavelet transform; lossless JPEG; lossless adaptive linear predictor schemes; lossless image compression; minimum weighted entropy; optical decomposition level; pixel value; predicted pixel intensity; prediction error; Arithmetic; Computer science; Distributed computing; Entropy; Image analysis; Image coding; Nonlinear filters; Transform coding; Wavelet analysis; Wavelet transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Compression Conference, 2003. Proceedings. DCC 2003
ISSN
1068-0314
Print_ISBN
0-7695-1896-6
Type
conf
DOI
10.1109/DCC.2003.1194064
Filename
1194064
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