A new image compression algorithm based on an adaptive vector quantization is presented. A novel efficient on-line codebook refining mechanism, called 'Gold-Washing' (GW) mechanism, including the GW algorithm which works on a dynamic codebook, called the GW codebook, is presented and implemented. This mechanism is universal so that it is suitable for any type of input data sources and is adaptive so that no source statistics transmission is needed. The asymptotic optimality of GW mechanism has been proven for not only memoryless (i.i.d.) sources but also stationary, ergodic sources. The efficiency and time complexity of the GW mechanism are analyzed. Based on this mechanism, an efficient hybrid adaptive vector quantizer which incorporates with other coding techniques such as a basic VQ with a large auxiliary codebook, called universal-mother (UM) codebook, as a new codeword generator, quadtree- based hierarchial decomposition, and classification is designed for image coding applications. From the experimental results, the performance of out image compression algorithm is competitive to and even better than those of JPEG and other coding algorithms, especially in low bit rate applications. The coded results with but rate of 0.120- 0.150 bits per pixel and acceptable image quality can be achieved.