Progressive Wavelet Image Coding
Based on a Conditional Probability Model
Robert W Buccigrossi
and
Eero P Simoncelli
Published in:
Proc. Int'l Conf. Acoustics Speech and Signal Processing
Munich, Germany. April 21-24, 1997.
© IEEE Signal Processing Society
Subsequent full-length journal publication:
IEEE Trans. Image Processing, 1999.
We present a wavelet image coder based on an explicit model of the
conditional statistical relationships between coefficients in
different subbands. In particular, we construct a parameterized model
for the conditional probability of a coefficient given coefficients at
a coarser scale. Subband coefficients are encoded one bitplane at a
time using a non-adaptive arithmetic encoder. The overall ordering of
bitplanes is determined by the ratio of their encoded variance to
compressed size. We show rate-distortion comparisons of the coder to
first and second-order theoretical entropy bounds and the EZW coder.
The coder is inherently embedded, and should prove useful in
applications requiring progressive transmission.
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