Engineering Applications of Artificial Intelligence
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A new class of wavelet filters, shift-invariant wavelet filters, is proposed for the purpose of image coding. The existing approaches obtain shift-invariant wavelet transform by finding the path in the full decomposition tree that minimizes the shift-variance with respect to a given cost function. This procedure is signal dependent and is inefficient for image coding, since the subband decomposition has to be performed for all shifts of input image during processing time. The shift-invariant wavelet transform proposed has a better shift-invariant property compared with the conventional dyadic wavelet transform without changing the dyadic structure. It is also independent of the input images. Experimental results in image coding show that the shift-invariant wavelet transform has a better energy compaction property. Two bit-allocation schemes, which are suitable for the proposed shift-invariant wavelet transform coding, are proposed and evaluated.