In this paper, a real-time wavelet image compression algorithm using vector quantization and its VLSI architecture are proposed. The proposed zerotree wavelet vector quantization (WVQ) algorithm focuses on the problem of how to reduce the computation time to encode wavelet images with high coding efficiency. A conventional wavelet image-compression algorithm exploits the tree structure of wavelet coefficients coupled with scalar quantization. However, they can not provide the real-time computation because they use iterative methods to decide zerotrees. In contrast, the zerotree WVQ algorithm predicts in real-time zero-vector trees of insignificant wavelet vectors by a noniterative decision rule and then encodes significant wavelet vectors by the classified VQ. These cause the zerotree WVQ algorithm to provide the best compromise between the coding performance and the computation time. The noniterative decision rule was extracted by the simulation results, which are based on the statistical characteristics of wavelet images. Moreover, the zerotree WVQ exploits the multistage VQ to encode the lowest frequency subband, which is generally known to be robust to wireless channel errors. The proposed WVQ VLSI architecture has only one VQ module to execute in real-time the proposed zerotree WVQ algorithm by utilizing the vacant cycles for zero-vector trees which are not transmitted. And the VQ module has only L + 1 processing elements (PE's) for the real-time minimum distance calculation, where the codebook size is L. L PE's are for Euclidean distance calculation and a PE is for parallel distance comparison. Compared with conventional architectures, the proposed VLSI architectures has very cost effective hardware (H/W) to calculate zerotree WVQ algorithm in real time. Therefore, the zerotree WVQ algorithm and its VLSI architectures are very suitable to wireless image communication, because they provide high coding efficiency, real-time computation, and cost-effective H/W.