Discrete wavelet transform is an ideal tool for multi-resolution representation of image signals. Some promising results have been recently reported on the application of wavelet transform for image compression. In this paper, we propose a new wavelet coding technique for image compression. The proposed scheme has the advantages of improved coding performance and reduced computational complexity. The input image is first decomposed into a pyramid structure with three layers using a 2-D wavelet transform. A block size of 2$+m$/ - 3 (m $EQ 1, 2, 3) is used for each orientation sub-image at the m-th layer to form 64-D vectors by combining the corresponding blocks in all the sub-images. The 64-D vectors are then encoded using 16-D non-linear interpolative vector quantization (NIVQ). At the decoder, the indices are used to reconstruct the 64-D vectors directly from a 64-D codebook designed using a non-linear interpolative technique. The proposed scheme not only exploits the correlation among the wavelet sub-images but also preserves the high frequency sub-images. Simulation results show that the reconstructed image of a superior quality can be obtained at a compression ratio of about 100:1.
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