Embedded image coding using zerotrees of wavelet coefficients
Shapiro, J.M.
David Sarnoff Res. Center, Princeton, NJ;
This paper appears in: Signal Processing, IEEE Transactions on
Publication Date: Dec 1993
Volume: 41,
Issue: 12
On page(s): 3445-3462
ISSN: 1053-587X
References Cited: 35
CODEN: ITPRED
INSPEC Accession Number: 4672587
Digital Object Identifier: 10.1109/78.258085
Current Version Published: 2002-08-06
Abstract
The embedded zerotree wavelet algorithm (EZW) is a simple, yet
remarkably effective, image compression algorithm, having the property
that the bits in the bit stream are generated in order of importance,
yielding a fully embedded code. The embedded code represents a sequence
of binary decisions that distinguish an image from the
“null” image. Using an embedded coding algorithm, an encoder
can terminate the encoding at any point thereby allowing a target rate
or target distortion metric to be met exactly. Also, given a bit stream,
the decoder can cease decoding at any point in the bit stream and still
produce exactly the same image that would have been encoded at the bit
rate corresponding to the truncated bit stream. In addition to producing
a fully embedded bit stream, the EZW consistently produces compression
results that are competitive with virtually all known compression
algorithms on standard test images. Yet this performance is achieved
with a technique that requires absolutely no training, no pre-stored
tables or codebooks, and requires no prior knowledge of the image
source. The EZW algorithm is based on four key concepts: (1) a discrete
wavelet transform or hierarchical subband decomposition, (2) prediction
of the absence of significant information across scales by exploiting
the self-similarity inherent in images, (3) entropy-coded
successive-approximation quantization, and (4) universal lossless data
compression which is achieved via adaptive arithmetic coding
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