We analyze the design issues for the SPIHT (set partitioning in hierarchical trees) coding, one of the best-regarded embedded-wavelet-based algorithms in the literature. Equipped with the multiresolution decomposition, progressive scalar quantization, and adaptive arithmetic coding, SPIHT generates highly compact scalable bitstreams suitable for real-time multimedia applications. The design parameters at each stage of SPIHT greatly influence its performance in terms of compression efficiency and computational complexity. We first evaluate two important classes of wavelet filters, orthogonal and biorthogonal. Orthogonal filters are energy-preserving, while biorthogonal linear-phase filters allow symmetric extension across the boundary. Among the various properties of wavelets pertaining to coding, we investigate the effects of energy compaction, energy conservation, and symmetric extension, respectively. Second, the magnitude of biorthogonal wavelet coefficients may not faithfully reflect their actual significance. We explore a scaling scheme in quantization that minimizes the overall mean squared error. Finally, the contribution of entropy coding is measured.