Wavelet Transform Coding With Linear Prediction And The Optimal Choice Of Wavelet Basis

Wavelet transform based coding has shown to be a promising method in low bit rate data compression. By using its multiresolution characteristics and the dependencies among subbands, the important visual features can be reconstructed at high compression ratio. In this paper, we propose a new wavelet transform coding scheme which exploits the linear prediction model for the existing dependencies across subbands. The main advantage of this algorithm is the low computational complexity which meets the requirement of VLSI implementation. As a result, the employment of our coding scheme makes real-time image processing achievable. In addition, the choice of optimal wavelet basis function is essential in wavelet compression. We address a new evaluation criterion "wavelet transform coding gain" which is based on the relationship between scalar quantization error and vector quantization error of our coding scheme. From our simulation results, it shows a strong correlation between wavelet transform coding gain and reconstruction quality.