Wavelet coding with region classification using low-complexity prediction model

A novel wavelet transform coding method based on the classification of different wavelet amplitude regions is presented. By using a low-complexity but efficient prediction model, we can distinguish different wavelet amplitude regions at the upper subbands. Therefore, adaptive quantizers can be used for different regions to achieve better reconstruction quality. The main advantage of this algorithm is the localized and modular structure 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 adaptive bit allocation is also discussed to achieve minimum quantization error.