To be able to compact large amounts of multimedia data and route it through a busy network at interactive rates has emerged as one of the biggest technological challenges of our times. Recently, there has been much activity in the areas of theoretical compression models using wavelets, evaluation of suitable wavelets for compression, fast real- time compression/decompression systems, and parallelized VLSI algorithms. Little work has been donee towards integrating these developments into a tightly coupled optimized scheme. We take a unified approach to developing a real-time compression/transmission system using a tight coupling of hierarchical vector quantization (HVQ) on discrete wavelet transformed images. We simultaneously optimize for speed, performance and scalability on several fronts, e.g. choice of wavelet, parallelizability, and efficient VLSI implementation. In doing so we demonstrate a speedup of O(logL), as well as reduce storage by a factor of O(log)L3. To achieve this we argue that the simplest wavelets, i.e. the Haar bases suffice for our scheme, because HVQ retains detail coefficients.We also show how to integrate the algorithm into the parallel graphics library, in order to achieve parallelized compression and progressive transmission of images.