Shapiro, Jerome M. Embedded image coding using zerotrees of wavelet coefficients. (English) Zbl 0841.94020 IEEE Trans. Signal Process. 41, No. 12, 3445-3462 (1993). 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. Cited in 1 ReviewCited in 95 Documents MSC: 94A12 Signal theory (characterization, reconstruction, filtering, etc.) Keywords:embedded zerotree wavelet; embedded zerotree wavelet algorithm; discrete wavelet transform; hierarchical subband decomposition; data compression PDFBibTeX XMLCite \textit{J. M. Shapiro}, IEEE Trans. Signal Process. 41, No. 12, 3445--3462 (1993; Zbl 0841.94020) Full Text: DOI