Generalized variable dimensional set partitioning for embedded wavelet image compression

A vector enhancement of Said and Pearlman´s (1996) set partitioning in hierarchical trees (SPIHT) methodology, named VSPIHT, has recently been proposed for embedded wavelet image compression. While the VSPIHT algorithm works better than scalar SPIHT for most images, a common vector dimension to use for coding an entire image may not be optimal. Since statistics vary widely within an image, a greater efficiency can be achieved if different vector dimensions are used for coding the wavelet coefficients from different portions of the image. We present a generalized methodology for developing a variable dimensional set partitioning coder, where different parts of an image may be coded in different vectoring modes, with different scale factors, and up to different number of passes. A Lagrangian rate-distortion criterion is used to make the optimum coding choices. Coding passes are made jointly for the vectoring modes to produce an embedded bitstream