Priority based vector quantization of wavelet coefficients

Wavelet transform is an efficient tool for image compression. Wavelet transform gives multiresolution image decomposition, which can be exploited through vector quantization to achieve high compression ratio. For vector quantization of wavelet coefficients vectors are formed by either coefficients at same level, different location or different level, same location. This paper compares the two methods and shows that because of wavelet properties, vector quantization can still improve compression results by coding only important vectors for reconstruction. Thus giving priority to the important vectors higher compression can be achieved at better quality. The algorithm is also useful for embedded vector quantization coding of wavelet coefficients.