A novel entropy-constrained adaptive quantization scheme for wavelet pyramid image coding

The orthogonal wavelet transform with filters of nonlinear phase gives poor visual results in low bit rate image coding. The biorthogonal wavelet is a good substitute, which is, however essentially nonorthogonal. A greedy steepest descent algorithm is proposed to design an adaptive quantization scheme based on the actual statistics of the input image. Since the L² norm of the quantization error is not preserved through the nonorthogonal transform, a quantization error estimation formula considering the characteristic value of the reconstruction filters is derived to incorporate the adaptive quantization scheme. Computer simulation results demonstrate significant SNR gains over standard coding techniques, and comparable visual improvements