Some adjacent image blocks may have the same address when ceding them with vector quantization（VQ）

especially in the stationary and uniform regions of an image. This paper proposes a correlation vector quantization scheme to decorrelate the addresses of adjacent coded blocks.Correlation codebook and improved self-organizing feature maps（ISOFM） codebook are sued to encode the four adjacent blocks simutaneously in a window.For a typical image"Lenna"

the computational quantity during the coding process is reduced by a factor of 2 and the bit rate is reduced by about 40% over the memoryless VQ. Since preferential measures are taken to the vectors belonging to the edge classes in the training process of Kohonen’s self-organization neural network

the subjective quality of the decoded image is significatly improved.