December 2002
Intermediate to advanced
454 pages
25h 39m
English
Content preview from Lossless Compression Handbook
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CHAPTER 9 / LOSSLESS IMAGE COMPRESSION 219
in the linear combination are determined using a LMS-based algorithm. The prediction errors of
the subpredictors are modeled as Laplacian distributions and the
a posteriori
probability of the
prediction error is used as the combination coefficient in the linear blending of predictors. The
performance of this algorithm was found to be comparable to that of CALIC [37].
Deng and Ye [44] used a Lagrange multiplier method in the linear combination of subpredictors.
If
pj(n)
is the prediction of the nth pixel using the jth subpredictor, then
ej(n)
is the corresponding
prediction error. The linear
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