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Embedded image coding using zerotrees of wavelet coefficients. (English) Zbl 0841.94020
This paper addresses the two-fold problem of 1) obtaining the best image quality for a given bit rate, and 2) accomplishing this task in an embedded fashion, i.e., in such a way that all encodings of the same image at lower bit rates are embedded in the beginning of the bit stream for the target bit rate.
The embedded zerotree wavelet 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.

MSC:
94A12 Signal theory (characterization, reconstruction, filtering, etc.)
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