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This paper introduces a new scheme for still image compression based on Vector Quantisation (VQ). The new scheme first vector quantised the image, then the indices obtained from quantisation are compressed and transmitted. The indices are used as a classifier to identif,' the active areas of the image. The residual of active areas are vector quantised in the second step and the indices generated are transmitted. The advantage of new scheme is to present the active areas of the coded image accurately without overhead requirement This scheme shows better subjective and objective in comparison with similar VQ schemes.

The indices obtained by tree-structured vector quantisation (TSVQ) have an interesting property that enables them to give information about the correlation between two image blocks. Iftwo image blocks are highly correlated, they may have an identical index, or the same ancestors. The existence of high inter-block correlation in natural images results in having neighboring blocks with the same genealogy. This characteristic can be used to compress the indices. This paper introduces a novel method to exploit the genealogical relation between the image block indices obtained from a TSVQ. The performance of this scheme in terms of PSNR versus average rate was compared with some other similar image coders. The results show that this scheme has better compression capability in terms of objective and subjective quality over these schemes at bit rates less than 0.3 bpp.