DocumentCode :
1394224
Title :
Lossless compression of video sequences
Author :
Memon, Nasir D. ; Sayood, Khalid
Author_Institution :
Dept. of Comput. Sci., Northern Illinois Univ., DeKalb, IL, USA
Volume :
44
Issue :
10
fYear :
1996
fDate :
10/1/1996 12:00:00 AM
Firstpage :
1340
Lastpage :
1345
Abstract :
We investigate lossless compression schemes for video sequences. A simple adaptive prediction scheme is presented that exploits temporal correlations or spectral correlations in addition to spatial correlations. It is seen that even with motion compensation, schemes that utilize only temporal correlations do not perform significantly better than schemes that utilize only spectral correlations. Hence, we look at hybrid schemes that make use of both spectral and temporal correlations. The hybrid schemes give significant improvement in performance over other techniques. Besides prediction schemes, we also look at some simple error modeling techniques that take into account prediction errors made in spectrally and/or temporally adjacent pixels in order to efficiently encode the prediction residual. Implementation results on standard test sequences indicate that significant improvements can be obtained by the proposed techniques
Keywords :
adaptive systems; coding errors; correlation methods; data compression; error statistics; image sequences; motion compensation; prediction theory; spectral analysis; video coding; adaptive prediction; error modeling techniques; hybrid schemes; lossless compression; motion compensation; performance; prediction errors; prediction residual encoding; spatial correlations; spectral correlations; standard test sequences; temporal correlations; video sequences; Biomedical imaging; Facsimile; Image coding; Motion compensation; Predictive models; Redundancy; Space technology; Testing; Video compression; Video sequences;
fLanguage :
English
Journal_Title :
Communications, IEEE Transactions on
Publisher :
ieee
ISSN :
0090-6778
Type :
jour
DOI :
10.1109/26.539775
Filename :
539775
Link To Document :
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